1 2 3 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 4 #include <petsc/private/vecimpl.h> 5 #include <petsc/private/isimpl.h> 6 #include <petscblaslapack.h> 7 #include <petscsf.h> 8 9 /*MC 10 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 11 12 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 13 and MATMPIAIJ otherwise. As a result, for single process communicators, 14 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 15 for communicators controlling multiple processes. It is recommended that you call both of 16 the above preallocation routines for simplicity. 17 18 Options Database Keys: 19 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 20 21 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 22 enough exist. 23 24 Level: beginner 25 26 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ 27 M*/ 28 29 /*MC 30 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 31 32 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 33 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 34 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 35 for communicators controlling multiple processes. It is recommended that you call both of 36 the above preallocation routines for simplicity. 37 38 Options Database Keys: 39 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 40 41 Level: beginner 42 43 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 44 M*/ 45 46 PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 51 PetscFunctionBegin; 52 if (mat->A) { 53 ierr = MatSetBlockSizes(mat->A,rbs,cbs);CHKERRQ(ierr); 54 ierr = MatSetBlockSizes(mat->B,rbs,1);CHKERRQ(ierr); 55 } 56 PetscFunctionReturn(0); 57 } 58 59 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 60 { 61 PetscErrorCode ierr; 62 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 63 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 64 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 65 const PetscInt *ia,*ib; 66 const MatScalar *aa,*bb; 67 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 68 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 69 70 PetscFunctionBegin; 71 *keptrows = 0; 72 ia = a->i; 73 ib = b->i; 74 for (i=0; i<m; i++) { 75 na = ia[i+1] - ia[i]; 76 nb = ib[i+1] - ib[i]; 77 if (!na && !nb) { 78 cnt++; 79 goto ok1; 80 } 81 aa = a->a + ia[i]; 82 for (j=0; j<na; j++) { 83 if (aa[j] != 0.0) goto ok1; 84 } 85 bb = b->a + ib[i]; 86 for (j=0; j <nb; j++) { 87 if (bb[j] != 0.0) goto ok1; 88 } 89 cnt++; 90 ok1:; 91 } 92 ierr = MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 93 if (!n0rows) PetscFunctionReturn(0); 94 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 95 cnt = 0; 96 for (i=0; i<m; i++) { 97 na = ia[i+1] - ia[i]; 98 nb = ib[i+1] - ib[i]; 99 if (!na && !nb) continue; 100 aa = a->a + ia[i]; 101 for (j=0; j<na;j++) { 102 if (aa[j] != 0.0) { 103 rows[cnt++] = rstart + i; 104 goto ok2; 105 } 106 } 107 bb = b->a + ib[i]; 108 for (j=0; j<nb; j++) { 109 if (bb[j] != 0.0) { 110 rows[cnt++] = rstart + i; 111 goto ok2; 112 } 113 } 114 ok2:; 115 } 116 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 117 PetscFunctionReturn(0); 118 } 119 120 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 121 { 122 PetscErrorCode ierr; 123 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 124 125 PetscFunctionBegin; 126 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 127 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 128 } else { 129 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 130 } 131 PetscFunctionReturn(0); 132 } 133 134 135 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 136 { 137 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 138 PetscErrorCode ierr; 139 PetscInt i,rstart,nrows,*rows; 140 141 PetscFunctionBegin; 142 *zrows = NULL; 143 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 144 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 145 for (i=0; i<nrows; i++) rows[i] += rstart; 146 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 147 PetscFunctionReturn(0); 148 } 149 150 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 151 { 152 PetscErrorCode ierr; 153 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 154 PetscInt i,n,*garray = aij->garray; 155 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 156 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 157 PetscReal *work; 158 159 PetscFunctionBegin; 160 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 161 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 162 if (type == NORM_2) { 163 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 164 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 165 } 166 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 167 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 168 } 169 } else if (type == NORM_1) { 170 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 171 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 172 } 173 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 174 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 175 } 176 } else if (type == NORM_INFINITY) { 177 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 178 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 179 } 180 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 181 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 182 } 183 184 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 185 if (type == NORM_INFINITY) { 186 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 187 } else { 188 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 189 } 190 ierr = PetscFree(work);CHKERRQ(ierr); 191 if (type == NORM_2) { 192 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 193 } 194 PetscFunctionReturn(0); 195 } 196 197 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 198 { 199 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 200 IS sis,gis; 201 PetscErrorCode ierr; 202 const PetscInt *isis,*igis; 203 PetscInt n,*iis,nsis,ngis,rstart,i; 204 205 PetscFunctionBegin; 206 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 207 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 208 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 209 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 210 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 211 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 212 213 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 214 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 215 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 216 n = ngis + nsis; 217 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 218 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 219 for (i=0; i<n; i++) iis[i] += rstart; 220 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 221 222 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 223 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 224 ierr = ISDestroy(&sis);CHKERRQ(ierr); 225 ierr = ISDestroy(&gis);CHKERRQ(ierr); 226 PetscFunctionReturn(0); 227 } 228 229 /* 230 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 231 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 232 233 Only for square matrices 234 235 Used by a preconditioner, hence PETSC_EXTERN 236 */ 237 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 238 { 239 PetscMPIInt rank,size; 240 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 241 PetscErrorCode ierr; 242 Mat mat; 243 Mat_SeqAIJ *gmata; 244 PetscMPIInt tag; 245 MPI_Status status; 246 PetscBool aij; 247 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 248 249 PetscFunctionBegin; 250 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 251 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 252 if (!rank) { 253 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 254 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 255 } 256 if (reuse == MAT_INITIAL_MATRIX) { 257 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 258 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 259 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 260 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 261 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 262 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 263 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 264 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 265 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 266 267 rowners[0] = 0; 268 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 269 rstart = rowners[rank]; 270 rend = rowners[rank+1]; 271 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 272 if (!rank) { 273 gmata = (Mat_SeqAIJ*) gmat->data; 274 /* send row lengths to all processors */ 275 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 276 for (i=1; i<size; i++) { 277 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 278 } 279 /* determine number diagonal and off-diagonal counts */ 280 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 281 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 282 jj = 0; 283 for (i=0; i<m; i++) { 284 for (j=0; j<dlens[i]; j++) { 285 if (gmata->j[jj] < rstart) ld[i]++; 286 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 287 jj++; 288 } 289 } 290 /* send column indices to other processes */ 291 for (i=1; i<size; i++) { 292 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 293 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 294 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 295 } 296 297 /* send numerical values to other processes */ 298 for (i=1; i<size; i++) { 299 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 300 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 301 } 302 gmataa = gmata->a; 303 gmataj = gmata->j; 304 305 } else { 306 /* receive row lengths */ 307 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 308 /* receive column indices */ 309 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 310 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 311 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 312 /* determine number diagonal and off-diagonal counts */ 313 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 314 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 315 jj = 0; 316 for (i=0; i<m; i++) { 317 for (j=0; j<dlens[i]; j++) { 318 if (gmataj[jj] < rstart) ld[i]++; 319 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 320 jj++; 321 } 322 } 323 /* receive numerical values */ 324 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 325 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 326 } 327 /* set preallocation */ 328 for (i=0; i<m; i++) { 329 dlens[i] -= olens[i]; 330 } 331 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 332 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 333 334 for (i=0; i<m; i++) { 335 dlens[i] += olens[i]; 336 } 337 cnt = 0; 338 for (i=0; i<m; i++) { 339 row = rstart + i; 340 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 341 cnt += dlens[i]; 342 } 343 if (rank) { 344 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 345 } 346 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 347 ierr = PetscFree(rowners);CHKERRQ(ierr); 348 349 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 350 351 *inmat = mat; 352 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 353 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 354 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 355 mat = *inmat; 356 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 357 if (!rank) { 358 /* send numerical values to other processes */ 359 gmata = (Mat_SeqAIJ*) gmat->data; 360 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 361 gmataa = gmata->a; 362 for (i=1; i<size; i++) { 363 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 364 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 365 } 366 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 367 } else { 368 /* receive numerical values from process 0*/ 369 nz = Ad->nz + Ao->nz; 370 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 371 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 372 } 373 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 374 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 375 ad = Ad->a; 376 ao = Ao->a; 377 if (mat->rmap->n) { 378 i = 0; 379 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 380 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 381 } 382 for (i=1; i<mat->rmap->n; i++) { 383 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 384 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 385 } 386 i--; 387 if (mat->rmap->n) { 388 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 389 } 390 if (rank) { 391 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 392 } 393 } 394 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 395 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 396 PetscFunctionReturn(0); 397 } 398 399 /* 400 Local utility routine that creates a mapping from the global column 401 number to the local number in the off-diagonal part of the local 402 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 403 a slightly higher hash table cost; without it it is not scalable (each processor 404 has an order N integer array but is fast to acess. 405 */ 406 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 407 { 408 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 409 PetscErrorCode ierr; 410 PetscInt n = aij->B->cmap->n,i; 411 412 PetscFunctionBegin; 413 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 414 #if defined(PETSC_USE_CTABLE) 415 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 416 for (i=0; i<n; i++) { 417 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 418 } 419 #else 420 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 421 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 422 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 423 #endif 424 PetscFunctionReturn(0); 425 } 426 427 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 428 { \ 429 if (col <= lastcol1) low1 = 0; \ 430 else high1 = nrow1; \ 431 lastcol1 = col;\ 432 while (high1-low1 > 5) { \ 433 t = (low1+high1)/2; \ 434 if (rp1[t] > col) high1 = t; \ 435 else low1 = t; \ 436 } \ 437 for (_i=low1; _i<high1; _i++) { \ 438 if (rp1[_i] > col) break; \ 439 if (rp1[_i] == col) { \ 440 if (addv == ADD_VALUES) ap1[_i] += value; \ 441 else ap1[_i] = value; \ 442 goto a_noinsert; \ 443 } \ 444 } \ 445 if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 446 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 447 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 448 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 449 N = nrow1++ - 1; a->nz++; high1++; \ 450 /* shift up all the later entries in this row */ \ 451 for (ii=N; ii>=_i; ii--) { \ 452 rp1[ii+1] = rp1[ii]; \ 453 ap1[ii+1] = ap1[ii]; \ 454 } \ 455 rp1[_i] = col; \ 456 ap1[_i] = value; \ 457 A->nonzerostate++;\ 458 a_noinsert: ; \ 459 ailen[row] = nrow1; \ 460 } 461 462 463 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 464 { \ 465 if (col <= lastcol2) low2 = 0; \ 466 else high2 = nrow2; \ 467 lastcol2 = col; \ 468 while (high2-low2 > 5) { \ 469 t = (low2+high2)/2; \ 470 if (rp2[t] > col) high2 = t; \ 471 else low2 = t; \ 472 } \ 473 for (_i=low2; _i<high2; _i++) { \ 474 if (rp2[_i] > col) break; \ 475 if (rp2[_i] == col) { \ 476 if (addv == ADD_VALUES) ap2[_i] += value; \ 477 else ap2[_i] = value; \ 478 goto b_noinsert; \ 479 } \ 480 } \ 481 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 482 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 483 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 484 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 485 N = nrow2++ - 1; b->nz++; high2++; \ 486 /* shift up all the later entries in this row */ \ 487 for (ii=N; ii>=_i; ii--) { \ 488 rp2[ii+1] = rp2[ii]; \ 489 ap2[ii+1] = ap2[ii]; \ 490 } \ 491 rp2[_i] = col; \ 492 ap2[_i] = value; \ 493 B->nonzerostate++; \ 494 b_noinsert: ; \ 495 bilen[row] = nrow2; \ 496 } 497 498 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 499 { 500 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 501 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 502 PetscErrorCode ierr; 503 PetscInt l,*garray = mat->garray,diag; 504 505 PetscFunctionBegin; 506 /* code only works for square matrices A */ 507 508 /* find size of row to the left of the diagonal part */ 509 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 510 row = row - diag; 511 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 512 if (garray[b->j[b->i[row]+l]] > diag) break; 513 } 514 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 515 516 /* diagonal part */ 517 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 518 519 /* right of diagonal part */ 520 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 521 PetscFunctionReturn(0); 522 } 523 524 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 525 { 526 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 527 PetscScalar value; 528 PetscErrorCode ierr; 529 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 530 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 531 PetscBool roworiented = aij->roworiented; 532 533 /* Some Variables required in the macro */ 534 Mat A = aij->A; 535 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 536 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 537 MatScalar *aa = a->a; 538 PetscBool ignorezeroentries = a->ignorezeroentries; 539 Mat B = aij->B; 540 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 541 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 542 MatScalar *ba = b->a; 543 544 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 545 PetscInt nonew; 546 MatScalar *ap1,*ap2; 547 548 PetscFunctionBegin; 549 for (i=0; i<m; i++) { 550 if (im[i] < 0) continue; 551 #if defined(PETSC_USE_DEBUG) 552 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 553 #endif 554 if (im[i] >= rstart && im[i] < rend) { 555 row = im[i] - rstart; 556 lastcol1 = -1; 557 rp1 = aj + ai[row]; 558 ap1 = aa + ai[row]; 559 rmax1 = aimax[row]; 560 nrow1 = ailen[row]; 561 low1 = 0; 562 high1 = nrow1; 563 lastcol2 = -1; 564 rp2 = bj + bi[row]; 565 ap2 = ba + bi[row]; 566 rmax2 = bimax[row]; 567 nrow2 = bilen[row]; 568 low2 = 0; 569 high2 = nrow2; 570 571 for (j=0; j<n; j++) { 572 if (roworiented) value = v[i*n+j]; 573 else value = v[i+j*m]; 574 if (in[j] >= cstart && in[j] < cend) { 575 col = in[j] - cstart; 576 nonew = a->nonew; 577 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 578 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 579 } else if (in[j] < 0) continue; 580 #if defined(PETSC_USE_DEBUG) 581 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 582 #endif 583 else { 584 if (mat->was_assembled) { 585 if (!aij->colmap) { 586 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 587 } 588 #if defined(PETSC_USE_CTABLE) 589 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 590 col--; 591 #else 592 col = aij->colmap[in[j]] - 1; 593 #endif 594 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 595 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 596 col = in[j]; 597 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 598 B = aij->B; 599 b = (Mat_SeqAIJ*)B->data; 600 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 601 rp2 = bj + bi[row]; 602 ap2 = ba + bi[row]; 603 rmax2 = bimax[row]; 604 nrow2 = bilen[row]; 605 low2 = 0; 606 high2 = nrow2; 607 bm = aij->B->rmap->n; 608 ba = b->a; 609 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]); 610 } else col = in[j]; 611 nonew = b->nonew; 612 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 613 } 614 } 615 } else { 616 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 617 if (!aij->donotstash) { 618 mat->assembled = PETSC_FALSE; 619 if (roworiented) { 620 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 621 } else { 622 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 623 } 624 } 625 } 626 } 627 PetscFunctionReturn(0); 628 } 629 630 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 631 { 632 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 633 PetscErrorCode ierr; 634 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 635 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 636 637 PetscFunctionBegin; 638 for (i=0; i<m; i++) { 639 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 640 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 641 if (idxm[i] >= rstart && idxm[i] < rend) { 642 row = idxm[i] - rstart; 643 for (j=0; j<n; j++) { 644 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 645 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 646 if (idxn[j] >= cstart && idxn[j] < cend) { 647 col = idxn[j] - cstart; 648 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 649 } else { 650 if (!aij->colmap) { 651 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 652 } 653 #if defined(PETSC_USE_CTABLE) 654 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 655 col--; 656 #else 657 col = aij->colmap[idxn[j]] - 1; 658 #endif 659 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 660 else { 661 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 662 } 663 } 664 } 665 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 666 } 667 PetscFunctionReturn(0); 668 } 669 670 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 671 672 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 673 { 674 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 675 PetscErrorCode ierr; 676 PetscInt nstash,reallocs; 677 678 PetscFunctionBegin; 679 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 680 681 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 682 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 683 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 684 PetscFunctionReturn(0); 685 } 686 687 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 688 { 689 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 690 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 691 PetscErrorCode ierr; 692 PetscMPIInt n; 693 PetscInt i,j,rstart,ncols,flg; 694 PetscInt *row,*col; 695 PetscBool other_disassembled; 696 PetscScalar *val; 697 698 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 699 700 PetscFunctionBegin; 701 if (!aij->donotstash && !mat->nooffprocentries) { 702 while (1) { 703 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 704 if (!flg) break; 705 706 for (i=0; i<n; ) { 707 /* Now identify the consecutive vals belonging to the same row */ 708 for (j=i,rstart=row[j]; j<n; j++) { 709 if (row[j] != rstart) break; 710 } 711 if (j < n) ncols = j-i; 712 else ncols = n-i; 713 /* Now assemble all these values with a single function call */ 714 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 715 716 i = j; 717 } 718 } 719 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 720 } 721 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 722 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 723 724 /* determine if any processor has disassembled, if so we must 725 also disassemble ourselfs, in order that we may reassemble. */ 726 /* 727 if nonzero structure of submatrix B cannot change then we know that 728 no processor disassembled thus we can skip this stuff 729 */ 730 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 731 ierr = MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 732 if (mat->was_assembled && !other_disassembled) { 733 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 734 } 735 } 736 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 737 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 738 } 739 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 740 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 741 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 742 743 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 744 745 aij->rowvalues = 0; 746 747 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 748 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 749 750 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 751 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 752 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 753 ierr = MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 754 } 755 PetscFunctionReturn(0); 756 } 757 758 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 759 { 760 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 761 PetscErrorCode ierr; 762 763 PetscFunctionBegin; 764 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 765 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 766 PetscFunctionReturn(0); 767 } 768 769 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 770 { 771 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 772 PetscInt *lrows; 773 PetscInt r, len; 774 PetscErrorCode ierr; 775 776 PetscFunctionBegin; 777 /* get locally owned rows */ 778 ierr = MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);CHKERRQ(ierr); 779 /* fix right hand side if needed */ 780 if (x && b) { 781 const PetscScalar *xx; 782 PetscScalar *bb; 783 784 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 785 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 786 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 787 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 788 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 789 } 790 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 791 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 792 if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */ 793 PetscBool cong; 794 ierr = PetscLayoutCompare(A->rmap,A->cmap,&cong);CHKERRQ(ierr); 795 if (cong) A->congruentlayouts = 1; 796 else A->congruentlayouts = 0; 797 } 798 if ((diag != 0.0) && A->congruentlayouts) { 799 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 800 } else if (diag != 0.0) { 801 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 802 if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 803 for (r = 0; r < len; ++r) { 804 const PetscInt row = lrows[r] + A->rmap->rstart; 805 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 806 } 807 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 808 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 809 } else { 810 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 811 } 812 ierr = PetscFree(lrows);CHKERRQ(ierr); 813 814 /* only change matrix nonzero state if pattern was allowed to be changed */ 815 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 816 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 817 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 818 } 819 PetscFunctionReturn(0); 820 } 821 822 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 823 { 824 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 825 PetscErrorCode ierr; 826 PetscMPIInt n = A->rmap->n; 827 PetscInt i,j,r,m,p = 0,len = 0; 828 PetscInt *lrows,*owners = A->rmap->range; 829 PetscSFNode *rrows; 830 PetscSF sf; 831 const PetscScalar *xx; 832 PetscScalar *bb,*mask; 833 Vec xmask,lmask; 834 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 835 const PetscInt *aj, *ii,*ridx; 836 PetscScalar *aa; 837 838 PetscFunctionBegin; 839 /* Create SF where leaves are input rows and roots are owned rows */ 840 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 841 for (r = 0; r < n; ++r) lrows[r] = -1; 842 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 843 for (r = 0; r < N; ++r) { 844 const PetscInt idx = rows[r]; 845 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 846 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 847 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 848 } 849 rrows[r].rank = p; 850 rrows[r].index = rows[r] - owners[p]; 851 } 852 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 853 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 854 /* Collect flags for rows to be zeroed */ 855 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 856 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 857 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 858 /* Compress and put in row numbers */ 859 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 860 /* zero diagonal part of matrix */ 861 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 862 /* handle off diagonal part of matrix */ 863 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 864 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 865 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 866 for (i=0; i<len; i++) bb[lrows[i]] = 1; 867 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 868 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 869 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 870 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 871 if (x) { 872 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 873 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 874 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 875 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 876 } 877 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 878 /* remove zeroed rows of off diagonal matrix */ 879 ii = aij->i; 880 for (i=0; i<len; i++) { 881 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 882 } 883 /* loop over all elements of off process part of matrix zeroing removed columns*/ 884 if (aij->compressedrow.use) { 885 m = aij->compressedrow.nrows; 886 ii = aij->compressedrow.i; 887 ridx = aij->compressedrow.rindex; 888 for (i=0; i<m; i++) { 889 n = ii[i+1] - ii[i]; 890 aj = aij->j + ii[i]; 891 aa = aij->a + ii[i]; 892 893 for (j=0; j<n; j++) { 894 if (PetscAbsScalar(mask[*aj])) { 895 if (b) bb[*ridx] -= *aa*xx[*aj]; 896 *aa = 0.0; 897 } 898 aa++; 899 aj++; 900 } 901 ridx++; 902 } 903 } else { /* do not use compressed row format */ 904 m = l->B->rmap->n; 905 for (i=0; i<m; i++) { 906 n = ii[i+1] - ii[i]; 907 aj = aij->j + ii[i]; 908 aa = aij->a + ii[i]; 909 for (j=0; j<n; j++) { 910 if (PetscAbsScalar(mask[*aj])) { 911 if (b) bb[i] -= *aa*xx[*aj]; 912 *aa = 0.0; 913 } 914 aa++; 915 aj++; 916 } 917 } 918 } 919 if (x) { 920 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 921 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 922 } 923 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 924 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 925 ierr = PetscFree(lrows);CHKERRQ(ierr); 926 927 /* only change matrix nonzero state if pattern was allowed to be changed */ 928 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 929 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 930 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 931 } 932 PetscFunctionReturn(0); 933 } 934 935 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 936 { 937 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 938 PetscErrorCode ierr; 939 PetscInt nt; 940 941 PetscFunctionBegin; 942 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 943 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 944 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 945 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 946 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 947 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 948 PetscFunctionReturn(0); 949 } 950 951 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 952 { 953 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 954 PetscErrorCode ierr; 955 956 PetscFunctionBegin; 957 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 958 PetscFunctionReturn(0); 959 } 960 961 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 962 { 963 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 964 PetscErrorCode ierr; 965 966 PetscFunctionBegin; 967 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 968 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 969 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 970 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 971 PetscFunctionReturn(0); 972 } 973 974 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 975 { 976 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 977 PetscErrorCode ierr; 978 PetscBool merged; 979 980 PetscFunctionBegin; 981 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 982 /* do nondiagonal part */ 983 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 984 if (!merged) { 985 /* send it on its way */ 986 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 987 /* do local part */ 988 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 989 /* receive remote parts: note this assumes the values are not actually */ 990 /* added in yy until the next line, */ 991 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 992 } else { 993 /* do local part */ 994 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 995 /* send it on its way */ 996 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 997 /* values actually were received in the Begin() but we need to call this nop */ 998 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 999 } 1000 PetscFunctionReturn(0); 1001 } 1002 1003 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1004 { 1005 MPI_Comm comm; 1006 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1007 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1008 IS Me,Notme; 1009 PetscErrorCode ierr; 1010 PetscInt M,N,first,last,*notme,i; 1011 PetscMPIInt size; 1012 1013 PetscFunctionBegin; 1014 /* Easy test: symmetric diagonal block */ 1015 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1016 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1017 if (!*f) PetscFunctionReturn(0); 1018 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1019 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1020 if (size == 1) PetscFunctionReturn(0); 1021 1022 /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */ 1023 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1024 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1025 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1026 for (i=0; i<first; i++) notme[i] = i; 1027 for (i=last; i<M; i++) notme[i-last+first] = i; 1028 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1029 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1030 ierr = MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1031 Aoff = Aoffs[0]; 1032 ierr = MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1033 Boff = Boffs[0]; 1034 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1035 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1036 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1037 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1038 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1039 ierr = PetscFree(notme);CHKERRQ(ierr); 1040 PetscFunctionReturn(0); 1041 } 1042 1043 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1044 { 1045 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1046 PetscErrorCode ierr; 1047 1048 PetscFunctionBegin; 1049 /* do nondiagonal part */ 1050 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1051 /* send it on its way */ 1052 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1053 /* do local part */ 1054 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1055 /* receive remote parts */ 1056 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1057 PetscFunctionReturn(0); 1058 } 1059 1060 /* 1061 This only works correctly for square matrices where the subblock A->A is the 1062 diagonal block 1063 */ 1064 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1065 { 1066 PetscErrorCode ierr; 1067 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1068 1069 PetscFunctionBegin; 1070 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1071 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1072 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1073 PetscFunctionReturn(0); 1074 } 1075 1076 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1077 { 1078 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1079 PetscErrorCode ierr; 1080 1081 PetscFunctionBegin; 1082 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1083 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1084 PetscFunctionReturn(0); 1085 } 1086 1087 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1088 { 1089 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1090 PetscErrorCode ierr; 1091 1092 PetscFunctionBegin; 1093 #if defined(PETSC_USE_LOG) 1094 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1095 #endif 1096 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1097 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1098 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1099 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1100 #if defined(PETSC_USE_CTABLE) 1101 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1102 #else 1103 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1104 #endif 1105 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1106 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1107 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1108 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1109 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1110 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1111 1112 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1115 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1116 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1117 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1118 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1119 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1120 #if defined(PETSC_HAVE_ELEMENTAL) 1121 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1122 #endif 1123 #if defined(PETSC_HAVE_HYPRE) 1124 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);CHKERRQ(ierr); 1125 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);CHKERRQ(ierr); 1126 #endif 1127 PetscFunctionReturn(0); 1128 } 1129 1130 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1131 { 1132 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1133 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1134 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1135 PetscErrorCode ierr; 1136 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1137 int fd; 1138 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1139 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1140 PetscScalar *column_values; 1141 PetscInt message_count,flowcontrolcount; 1142 FILE *file; 1143 1144 PetscFunctionBegin; 1145 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1146 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1147 nz = A->nz + B->nz; 1148 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1149 if (!rank) { 1150 header[0] = MAT_FILE_CLASSID; 1151 header[1] = mat->rmap->N; 1152 header[2] = mat->cmap->N; 1153 1154 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1155 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1156 /* get largest number of rows any processor has */ 1157 rlen = mat->rmap->n; 1158 range = mat->rmap->range; 1159 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1160 } else { 1161 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1162 rlen = mat->rmap->n; 1163 } 1164 1165 /* load up the local row counts */ 1166 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1167 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1168 1169 /* store the row lengths to the file */ 1170 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1171 if (!rank) { 1172 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1173 for (i=1; i<size; i++) { 1174 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1175 rlen = range[i+1] - range[i]; 1176 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1177 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1178 } 1179 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1180 } else { 1181 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1182 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1183 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1184 } 1185 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1186 1187 /* load up the local column indices */ 1188 nzmax = nz; /* th processor needs space a largest processor needs */ 1189 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1190 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1191 cnt = 0; 1192 for (i=0; i<mat->rmap->n; i++) { 1193 for (j=B->i[i]; j<B->i[i+1]; j++) { 1194 if ((col = garray[B->j[j]]) > cstart) break; 1195 column_indices[cnt++] = col; 1196 } 1197 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1198 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1199 } 1200 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1201 1202 /* store the column indices to the file */ 1203 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1204 if (!rank) { 1205 MPI_Status status; 1206 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1207 for (i=1; i<size; i++) { 1208 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1209 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1210 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1211 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1212 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1213 } 1214 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1215 } else { 1216 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1217 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1218 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1219 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1220 } 1221 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1222 1223 /* load up the local column values */ 1224 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1225 cnt = 0; 1226 for (i=0; i<mat->rmap->n; i++) { 1227 for (j=B->i[i]; j<B->i[i+1]; j++) { 1228 if (garray[B->j[j]] > cstart) break; 1229 column_values[cnt++] = B->a[j]; 1230 } 1231 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1232 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1233 } 1234 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1235 1236 /* store the column values to the file */ 1237 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1238 if (!rank) { 1239 MPI_Status status; 1240 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1241 for (i=1; i<size; i++) { 1242 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1243 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1244 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1245 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1246 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1247 } 1248 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1249 } else { 1250 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1251 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1252 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1253 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1254 } 1255 ierr = PetscFree(column_values);CHKERRQ(ierr); 1256 1257 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1258 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1259 PetscFunctionReturn(0); 1260 } 1261 1262 #include <petscdraw.h> 1263 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1264 { 1265 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1266 PetscErrorCode ierr; 1267 PetscMPIInt rank = aij->rank,size = aij->size; 1268 PetscBool isdraw,iascii,isbinary; 1269 PetscViewer sviewer; 1270 PetscViewerFormat format; 1271 1272 PetscFunctionBegin; 1273 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1274 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1275 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1276 if (iascii) { 1277 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1278 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1279 MatInfo info; 1280 PetscBool inodes; 1281 1282 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1283 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1284 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1285 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1286 if (!inodes) { 1287 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1288 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1289 } else { 1290 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1291 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1292 } 1293 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1294 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1295 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1296 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1297 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1298 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1299 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1300 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1301 PetscFunctionReturn(0); 1302 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1303 PetscInt inodecount,inodelimit,*inodes; 1304 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1305 if (inodes) { 1306 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1307 } else { 1308 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1309 } 1310 PetscFunctionReturn(0); 1311 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1312 PetscFunctionReturn(0); 1313 } 1314 } else if (isbinary) { 1315 if (size == 1) { 1316 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1317 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1318 } else { 1319 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1320 } 1321 PetscFunctionReturn(0); 1322 } else if (isdraw) { 1323 PetscDraw draw; 1324 PetscBool isnull; 1325 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1326 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1327 if (isnull) PetscFunctionReturn(0); 1328 } 1329 1330 { 1331 /* assemble the entire matrix onto first processor. */ 1332 Mat A; 1333 Mat_SeqAIJ *Aloc; 1334 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1335 MatScalar *a; 1336 1337 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1338 if (!rank) { 1339 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1340 } else { 1341 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1342 } 1343 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1344 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1345 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1346 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1347 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1348 1349 /* copy over the A part */ 1350 Aloc = (Mat_SeqAIJ*)aij->A->data; 1351 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1352 row = mat->rmap->rstart; 1353 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1354 for (i=0; i<m; i++) { 1355 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1356 row++; 1357 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1358 } 1359 aj = Aloc->j; 1360 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1361 1362 /* copy over the B part */ 1363 Aloc = (Mat_SeqAIJ*)aij->B->data; 1364 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1365 row = mat->rmap->rstart; 1366 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1367 ct = cols; 1368 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1369 for (i=0; i<m; i++) { 1370 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1371 row++; 1372 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1373 } 1374 ierr = PetscFree(ct);CHKERRQ(ierr); 1375 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1376 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1377 /* 1378 Everyone has to call to draw the matrix since the graphics waits are 1379 synchronized across all processors that share the PetscDraw object 1380 */ 1381 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1382 if (!rank) { 1383 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1384 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1385 } 1386 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1387 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1388 ierr = MatDestroy(&A);CHKERRQ(ierr); 1389 } 1390 PetscFunctionReturn(0); 1391 } 1392 1393 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1394 { 1395 PetscErrorCode ierr; 1396 PetscBool iascii,isdraw,issocket,isbinary; 1397 1398 PetscFunctionBegin; 1399 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1400 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1401 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1402 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1403 if (iascii || isdraw || isbinary || issocket) { 1404 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1405 } 1406 PetscFunctionReturn(0); 1407 } 1408 1409 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1410 { 1411 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1412 PetscErrorCode ierr; 1413 Vec bb1 = 0; 1414 PetscBool hasop; 1415 1416 PetscFunctionBegin; 1417 if (flag == SOR_APPLY_UPPER) { 1418 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1419 PetscFunctionReturn(0); 1420 } 1421 1422 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1423 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1424 } 1425 1426 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1427 if (flag & SOR_ZERO_INITIAL_GUESS) { 1428 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1429 its--; 1430 } 1431 1432 while (its--) { 1433 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1434 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1435 1436 /* update rhs: bb1 = bb - B*x */ 1437 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1438 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1439 1440 /* local sweep */ 1441 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1442 } 1443 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1444 if (flag & SOR_ZERO_INITIAL_GUESS) { 1445 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1446 its--; 1447 } 1448 while (its--) { 1449 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1450 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1451 1452 /* update rhs: bb1 = bb - B*x */ 1453 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1454 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1455 1456 /* local sweep */ 1457 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1458 } 1459 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1460 if (flag & SOR_ZERO_INITIAL_GUESS) { 1461 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1462 its--; 1463 } 1464 while (its--) { 1465 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1466 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1467 1468 /* update rhs: bb1 = bb - B*x */ 1469 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1470 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1471 1472 /* local sweep */ 1473 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1474 } 1475 } else if (flag & SOR_EISENSTAT) { 1476 Vec xx1; 1477 1478 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1479 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1480 1481 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1482 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1483 if (!mat->diag) { 1484 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1485 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1486 } 1487 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1488 if (hasop) { 1489 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1490 } else { 1491 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1492 } 1493 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1494 1495 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1496 1497 /* local sweep */ 1498 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1499 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1500 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1501 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1502 1503 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1504 1505 matin->factorerrortype = mat->A->factorerrortype; 1506 PetscFunctionReturn(0); 1507 } 1508 1509 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1510 { 1511 Mat aA,aB,Aperm; 1512 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1513 PetscScalar *aa,*ba; 1514 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1515 PetscSF rowsf,sf; 1516 IS parcolp = NULL; 1517 PetscBool done; 1518 PetscErrorCode ierr; 1519 1520 PetscFunctionBegin; 1521 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1522 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1523 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1524 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1525 1526 /* Invert row permutation to find out where my rows should go */ 1527 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1528 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1529 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1530 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1531 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1532 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1533 1534 /* Invert column permutation to find out where my columns should go */ 1535 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1536 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1537 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1538 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1539 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1540 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1541 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1542 1543 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1544 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1545 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1546 1547 /* Find out where my gcols should go */ 1548 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1549 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1550 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1551 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1552 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1553 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1554 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1555 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1556 1557 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1558 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1559 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1560 for (i=0; i<m; i++) { 1561 PetscInt row = rdest[i],rowner; 1562 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1563 for (j=ai[i]; j<ai[i+1]; j++) { 1564 PetscInt cowner,col = cdest[aj[j]]; 1565 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1566 if (rowner == cowner) dnnz[i]++; 1567 else onnz[i]++; 1568 } 1569 for (j=bi[i]; j<bi[i+1]; j++) { 1570 PetscInt cowner,col = gcdest[bj[j]]; 1571 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1572 if (rowner == cowner) dnnz[i]++; 1573 else onnz[i]++; 1574 } 1575 } 1576 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1577 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1578 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1579 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1580 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1581 1582 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1583 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1584 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1585 for (i=0; i<m; i++) { 1586 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1587 PetscInt j0,rowlen; 1588 rowlen = ai[i+1] - ai[i]; 1589 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1590 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1591 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1592 } 1593 rowlen = bi[i+1] - bi[i]; 1594 for (j0=j=0; j<rowlen; j0=j) { 1595 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1596 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1597 } 1598 } 1599 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1600 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1601 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1602 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1603 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1604 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1605 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1606 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1607 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1608 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1609 *B = Aperm; 1610 PetscFunctionReturn(0); 1611 } 1612 1613 PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 1614 { 1615 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1616 PetscErrorCode ierr; 1617 1618 PetscFunctionBegin; 1619 ierr = MatGetSize(aij->B,NULL,nghosts);CHKERRQ(ierr); 1620 if (ghosts) *ghosts = aij->garray; 1621 PetscFunctionReturn(0); 1622 } 1623 1624 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1625 { 1626 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1627 Mat A = mat->A,B = mat->B; 1628 PetscErrorCode ierr; 1629 PetscReal isend[5],irecv[5]; 1630 1631 PetscFunctionBegin; 1632 info->block_size = 1.0; 1633 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1634 1635 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1636 isend[3] = info->memory; isend[4] = info->mallocs; 1637 1638 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1639 1640 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1641 isend[3] += info->memory; isend[4] += info->mallocs; 1642 if (flag == MAT_LOCAL) { 1643 info->nz_used = isend[0]; 1644 info->nz_allocated = isend[1]; 1645 info->nz_unneeded = isend[2]; 1646 info->memory = isend[3]; 1647 info->mallocs = isend[4]; 1648 } else if (flag == MAT_GLOBAL_MAX) { 1649 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1650 1651 info->nz_used = irecv[0]; 1652 info->nz_allocated = irecv[1]; 1653 info->nz_unneeded = irecv[2]; 1654 info->memory = irecv[3]; 1655 info->mallocs = irecv[4]; 1656 } else if (flag == MAT_GLOBAL_SUM) { 1657 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1658 1659 info->nz_used = irecv[0]; 1660 info->nz_allocated = irecv[1]; 1661 info->nz_unneeded = irecv[2]; 1662 info->memory = irecv[3]; 1663 info->mallocs = irecv[4]; 1664 } 1665 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1666 info->fill_ratio_needed = 0; 1667 info->factor_mallocs = 0; 1668 PetscFunctionReturn(0); 1669 } 1670 1671 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1672 { 1673 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1674 PetscErrorCode ierr; 1675 1676 PetscFunctionBegin; 1677 switch (op) { 1678 case MAT_NEW_NONZERO_LOCATIONS: 1679 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1680 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1681 case MAT_KEEP_NONZERO_PATTERN: 1682 case MAT_NEW_NONZERO_LOCATION_ERR: 1683 case MAT_USE_INODES: 1684 case MAT_IGNORE_ZERO_ENTRIES: 1685 MatCheckPreallocated(A,1); 1686 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1687 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1688 break; 1689 case MAT_ROW_ORIENTED: 1690 MatCheckPreallocated(A,1); 1691 a->roworiented = flg; 1692 1693 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1694 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1695 break; 1696 case MAT_NEW_DIAGONALS: 1697 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1698 break; 1699 case MAT_IGNORE_OFF_PROC_ENTRIES: 1700 a->donotstash = flg; 1701 break; 1702 case MAT_SPD: 1703 A->spd_set = PETSC_TRUE; 1704 A->spd = flg; 1705 if (flg) { 1706 A->symmetric = PETSC_TRUE; 1707 A->structurally_symmetric = PETSC_TRUE; 1708 A->symmetric_set = PETSC_TRUE; 1709 A->structurally_symmetric_set = PETSC_TRUE; 1710 } 1711 break; 1712 case MAT_SYMMETRIC: 1713 MatCheckPreallocated(A,1); 1714 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1715 break; 1716 case MAT_STRUCTURALLY_SYMMETRIC: 1717 MatCheckPreallocated(A,1); 1718 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1719 break; 1720 case MAT_HERMITIAN: 1721 MatCheckPreallocated(A,1); 1722 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1723 break; 1724 case MAT_SYMMETRY_ETERNAL: 1725 MatCheckPreallocated(A,1); 1726 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1727 break; 1728 case MAT_SUBMAT_SINGLEIS: 1729 A->submat_singleis = flg; 1730 break; 1731 default: 1732 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1733 } 1734 PetscFunctionReturn(0); 1735 } 1736 1737 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1738 { 1739 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1740 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1741 PetscErrorCode ierr; 1742 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1743 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1744 PetscInt *cmap,*idx_p; 1745 1746 PetscFunctionBegin; 1747 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1748 mat->getrowactive = PETSC_TRUE; 1749 1750 if (!mat->rowvalues && (idx || v)) { 1751 /* 1752 allocate enough space to hold information from the longest row. 1753 */ 1754 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1755 PetscInt max = 1,tmp; 1756 for (i=0; i<matin->rmap->n; i++) { 1757 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1758 if (max < tmp) max = tmp; 1759 } 1760 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1761 } 1762 1763 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1764 lrow = row - rstart; 1765 1766 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1767 if (!v) {pvA = 0; pvB = 0;} 1768 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1769 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1770 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1771 nztot = nzA + nzB; 1772 1773 cmap = mat->garray; 1774 if (v || idx) { 1775 if (nztot) { 1776 /* Sort by increasing column numbers, assuming A and B already sorted */ 1777 PetscInt imark = -1; 1778 if (v) { 1779 *v = v_p = mat->rowvalues; 1780 for (i=0; i<nzB; i++) { 1781 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1782 else break; 1783 } 1784 imark = i; 1785 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1786 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1787 } 1788 if (idx) { 1789 *idx = idx_p = mat->rowindices; 1790 if (imark > -1) { 1791 for (i=0; i<imark; i++) { 1792 idx_p[i] = cmap[cworkB[i]]; 1793 } 1794 } else { 1795 for (i=0; i<nzB; i++) { 1796 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1797 else break; 1798 } 1799 imark = i; 1800 } 1801 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1802 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1803 } 1804 } else { 1805 if (idx) *idx = 0; 1806 if (v) *v = 0; 1807 } 1808 } 1809 *nz = nztot; 1810 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1811 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1812 PetscFunctionReturn(0); 1813 } 1814 1815 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1816 { 1817 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1818 1819 PetscFunctionBegin; 1820 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1821 aij->getrowactive = PETSC_FALSE; 1822 PetscFunctionReturn(0); 1823 } 1824 1825 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1826 { 1827 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1828 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1829 PetscErrorCode ierr; 1830 PetscInt i,j,cstart = mat->cmap->rstart; 1831 PetscReal sum = 0.0; 1832 MatScalar *v; 1833 1834 PetscFunctionBegin; 1835 if (aij->size == 1) { 1836 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1837 } else { 1838 if (type == NORM_FROBENIUS) { 1839 v = amat->a; 1840 for (i=0; i<amat->nz; i++) { 1841 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1842 } 1843 v = bmat->a; 1844 for (i=0; i<bmat->nz; i++) { 1845 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1846 } 1847 ierr = MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1848 *norm = PetscSqrtReal(*norm); 1849 ierr = PetscLogFlops(2*amat->nz+2*bmat->nz);CHKERRQ(ierr); 1850 } else if (type == NORM_1) { /* max column norm */ 1851 PetscReal *tmp,*tmp2; 1852 PetscInt *jj,*garray = aij->garray; 1853 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1854 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1855 *norm = 0.0; 1856 v = amat->a; jj = amat->j; 1857 for (j=0; j<amat->nz; j++) { 1858 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1859 } 1860 v = bmat->a; jj = bmat->j; 1861 for (j=0; j<bmat->nz; j++) { 1862 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1863 } 1864 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1865 for (j=0; j<mat->cmap->N; j++) { 1866 if (tmp2[j] > *norm) *norm = tmp2[j]; 1867 } 1868 ierr = PetscFree(tmp);CHKERRQ(ierr); 1869 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1870 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1871 } else if (type == NORM_INFINITY) { /* max row norm */ 1872 PetscReal ntemp = 0.0; 1873 for (j=0; j<aij->A->rmap->n; j++) { 1874 v = amat->a + amat->i[j]; 1875 sum = 0.0; 1876 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1877 sum += PetscAbsScalar(*v); v++; 1878 } 1879 v = bmat->a + bmat->i[j]; 1880 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1881 sum += PetscAbsScalar(*v); v++; 1882 } 1883 if (sum > ntemp) ntemp = sum; 1884 } 1885 ierr = MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1886 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1887 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1888 } 1889 PetscFunctionReturn(0); 1890 } 1891 1892 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1893 { 1894 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1895 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1896 PetscErrorCode ierr; 1897 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1898 PetscInt cstart = A->cmap->rstart,ncol; 1899 Mat B; 1900 MatScalar *array; 1901 1902 PetscFunctionBegin; 1903 if (reuse == MAT_INPLACE_MATRIX && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1904 1905 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1906 ai = Aloc->i; aj = Aloc->j; 1907 bi = Bloc->i; bj = Bloc->j; 1908 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1909 PetscInt *d_nnz,*g_nnz,*o_nnz; 1910 PetscSFNode *oloc; 1911 PETSC_UNUSED PetscSF sf; 1912 1913 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1914 /* compute d_nnz for preallocation */ 1915 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1916 for (i=0; i<ai[ma]; i++) { 1917 d_nnz[aj[i]]++; 1918 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1919 } 1920 /* compute local off-diagonal contributions */ 1921 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1922 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1923 /* map those to global */ 1924 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1925 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1926 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1927 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1928 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1929 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1930 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1931 1932 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1933 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1934 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1935 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1936 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1937 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1938 } else { 1939 B = *matout; 1940 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1941 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1942 } 1943 1944 /* copy over the A part */ 1945 array = Aloc->a; 1946 row = A->rmap->rstart; 1947 for (i=0; i<ma; i++) { 1948 ncol = ai[i+1]-ai[i]; 1949 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1950 row++; 1951 array += ncol; aj += ncol; 1952 } 1953 aj = Aloc->j; 1954 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1955 1956 /* copy over the B part */ 1957 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 1958 array = Bloc->a; 1959 row = A->rmap->rstart; 1960 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 1961 cols_tmp = cols; 1962 for (i=0; i<mb; i++) { 1963 ncol = bi[i+1]-bi[i]; 1964 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1965 row++; 1966 array += ncol; cols_tmp += ncol; 1967 } 1968 ierr = PetscFree(cols);CHKERRQ(ierr); 1969 1970 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1971 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1972 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 1973 *matout = B; 1974 } else { 1975 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 1976 } 1977 PetscFunctionReturn(0); 1978 } 1979 1980 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1981 { 1982 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1983 Mat a = aij->A,b = aij->B; 1984 PetscErrorCode ierr; 1985 PetscInt s1,s2,s3; 1986 1987 PetscFunctionBegin; 1988 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1989 if (rr) { 1990 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1991 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1992 /* Overlap communication with computation. */ 1993 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1994 } 1995 if (ll) { 1996 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1997 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1998 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1999 } 2000 /* scale the diagonal block */ 2001 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2002 2003 if (rr) { 2004 /* Do a scatter end and then right scale the off-diagonal block */ 2005 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2006 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2007 } 2008 PetscFunctionReturn(0); 2009 } 2010 2011 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2012 { 2013 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2014 PetscErrorCode ierr; 2015 2016 PetscFunctionBegin; 2017 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2018 PetscFunctionReturn(0); 2019 } 2020 2021 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2022 { 2023 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2024 Mat a,b,c,d; 2025 PetscBool flg; 2026 PetscErrorCode ierr; 2027 2028 PetscFunctionBegin; 2029 a = matA->A; b = matA->B; 2030 c = matB->A; d = matB->B; 2031 2032 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2033 if (flg) { 2034 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2035 } 2036 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2037 PetscFunctionReturn(0); 2038 } 2039 2040 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2041 { 2042 PetscErrorCode ierr; 2043 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2044 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2045 2046 PetscFunctionBegin; 2047 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2048 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2049 /* because of the column compression in the off-processor part of the matrix a->B, 2050 the number of columns in a->B and b->B may be different, hence we cannot call 2051 the MatCopy() directly on the two parts. If need be, we can provide a more 2052 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2053 then copying the submatrices */ 2054 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2055 } else { 2056 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2057 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2058 } 2059 PetscFunctionReturn(0); 2060 } 2061 2062 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2063 { 2064 PetscErrorCode ierr; 2065 2066 PetscFunctionBegin; 2067 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2068 PetscFunctionReturn(0); 2069 } 2070 2071 /* 2072 Computes the number of nonzeros per row needed for preallocation when X and Y 2073 have different nonzero structure. 2074 */ 2075 PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz) 2076 { 2077 PetscInt i,j,k,nzx,nzy; 2078 2079 PetscFunctionBegin; 2080 /* Set the number of nonzeros in the new matrix */ 2081 for (i=0; i<m; i++) { 2082 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2083 nzx = xi[i+1] - xi[i]; 2084 nzy = yi[i+1] - yi[i]; 2085 nnz[i] = 0; 2086 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2087 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2088 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2089 nnz[i]++; 2090 } 2091 for (; k<nzy; k++) nnz[i]++; 2092 } 2093 PetscFunctionReturn(0); 2094 } 2095 2096 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2097 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2098 { 2099 PetscErrorCode ierr; 2100 PetscInt m = Y->rmap->N; 2101 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2102 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2103 2104 PetscFunctionBegin; 2105 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2106 PetscFunctionReturn(0); 2107 } 2108 2109 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2110 { 2111 PetscErrorCode ierr; 2112 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2113 PetscBLASInt bnz,one=1; 2114 Mat_SeqAIJ *x,*y; 2115 2116 PetscFunctionBegin; 2117 if (str == SAME_NONZERO_PATTERN) { 2118 PetscScalar alpha = a; 2119 x = (Mat_SeqAIJ*)xx->A->data; 2120 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2121 y = (Mat_SeqAIJ*)yy->A->data; 2122 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2123 x = (Mat_SeqAIJ*)xx->B->data; 2124 y = (Mat_SeqAIJ*)yy->B->data; 2125 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2126 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2127 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2128 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2129 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2130 } else { 2131 Mat B; 2132 PetscInt *nnz_d,*nnz_o; 2133 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2134 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2135 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2136 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2137 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2138 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2139 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2140 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2141 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2142 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2143 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2144 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2145 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2146 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2147 } 2148 PetscFunctionReturn(0); 2149 } 2150 2151 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2152 2153 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2154 { 2155 #if defined(PETSC_USE_COMPLEX) 2156 PetscErrorCode ierr; 2157 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2158 2159 PetscFunctionBegin; 2160 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2161 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2162 #else 2163 PetscFunctionBegin; 2164 #endif 2165 PetscFunctionReturn(0); 2166 } 2167 2168 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2169 { 2170 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2171 PetscErrorCode ierr; 2172 2173 PetscFunctionBegin; 2174 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2175 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2176 PetscFunctionReturn(0); 2177 } 2178 2179 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2180 { 2181 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2182 PetscErrorCode ierr; 2183 2184 PetscFunctionBegin; 2185 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2186 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2187 PetscFunctionReturn(0); 2188 } 2189 2190 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2191 { 2192 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2193 PetscErrorCode ierr; 2194 PetscInt i,*idxb = 0; 2195 PetscScalar *va,*vb; 2196 Vec vtmp; 2197 2198 PetscFunctionBegin; 2199 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2200 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2201 if (idx) { 2202 for (i=0; i<A->rmap->n; i++) { 2203 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2204 } 2205 } 2206 2207 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2208 if (idx) { 2209 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2210 } 2211 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2212 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2213 2214 for (i=0; i<A->rmap->n; i++) { 2215 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2216 va[i] = vb[i]; 2217 if (idx) idx[i] = a->garray[idxb[i]]; 2218 } 2219 } 2220 2221 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2222 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2223 ierr = PetscFree(idxb);CHKERRQ(ierr); 2224 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2225 PetscFunctionReturn(0); 2226 } 2227 2228 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2229 { 2230 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2231 PetscErrorCode ierr; 2232 PetscInt i,*idxb = 0; 2233 PetscScalar *va,*vb; 2234 Vec vtmp; 2235 2236 PetscFunctionBegin; 2237 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2238 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2239 if (idx) { 2240 for (i=0; i<A->cmap->n; i++) { 2241 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2242 } 2243 } 2244 2245 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2246 if (idx) { 2247 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2248 } 2249 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2250 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2251 2252 for (i=0; i<A->rmap->n; i++) { 2253 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2254 va[i] = vb[i]; 2255 if (idx) idx[i] = a->garray[idxb[i]]; 2256 } 2257 } 2258 2259 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2260 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2261 ierr = PetscFree(idxb);CHKERRQ(ierr); 2262 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2263 PetscFunctionReturn(0); 2264 } 2265 2266 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2267 { 2268 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2269 PetscInt n = A->rmap->n; 2270 PetscInt cstart = A->cmap->rstart; 2271 PetscInt *cmap = mat->garray; 2272 PetscInt *diagIdx, *offdiagIdx; 2273 Vec diagV, offdiagV; 2274 PetscScalar *a, *diagA, *offdiagA; 2275 PetscInt r; 2276 PetscErrorCode ierr; 2277 2278 PetscFunctionBegin; 2279 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2280 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2281 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2282 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2283 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2284 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2285 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2286 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2287 for (r = 0; r < n; ++r) { 2288 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2289 a[r] = diagA[r]; 2290 idx[r] = cstart + diagIdx[r]; 2291 } else { 2292 a[r] = offdiagA[r]; 2293 idx[r] = cmap[offdiagIdx[r]]; 2294 } 2295 } 2296 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2297 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2298 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2299 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2300 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2301 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2302 PetscFunctionReturn(0); 2303 } 2304 2305 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2306 { 2307 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2308 PetscInt n = A->rmap->n; 2309 PetscInt cstart = A->cmap->rstart; 2310 PetscInt *cmap = mat->garray; 2311 PetscInt *diagIdx, *offdiagIdx; 2312 Vec diagV, offdiagV; 2313 PetscScalar *a, *diagA, *offdiagA; 2314 PetscInt r; 2315 PetscErrorCode ierr; 2316 2317 PetscFunctionBegin; 2318 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2319 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2320 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2321 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2322 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2323 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2324 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2325 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2326 for (r = 0; r < n; ++r) { 2327 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2328 a[r] = diagA[r]; 2329 idx[r] = cstart + diagIdx[r]; 2330 } else { 2331 a[r] = offdiagA[r]; 2332 idx[r] = cmap[offdiagIdx[r]]; 2333 } 2334 } 2335 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2336 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2337 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2338 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2339 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2340 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2341 PetscFunctionReturn(0); 2342 } 2343 2344 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2345 { 2346 PetscErrorCode ierr; 2347 Mat *dummy; 2348 2349 PetscFunctionBegin; 2350 ierr = MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2351 *newmat = *dummy; 2352 ierr = PetscFree(dummy);CHKERRQ(ierr); 2353 PetscFunctionReturn(0); 2354 } 2355 2356 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2357 { 2358 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2359 PetscErrorCode ierr; 2360 2361 PetscFunctionBegin; 2362 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2363 A->factorerrortype = a->A->factorerrortype; 2364 PetscFunctionReturn(0); 2365 } 2366 2367 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2368 { 2369 PetscErrorCode ierr; 2370 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2371 2372 PetscFunctionBegin; 2373 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2374 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2375 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2376 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2377 PetscFunctionReturn(0); 2378 } 2379 2380 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2381 { 2382 PetscFunctionBegin; 2383 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2384 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2385 PetscFunctionReturn(0); 2386 } 2387 2388 /*@ 2389 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2390 2391 Collective on Mat 2392 2393 Input Parameters: 2394 + A - the matrix 2395 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2396 2397 Level: advanced 2398 2399 @*/ 2400 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2401 { 2402 PetscErrorCode ierr; 2403 2404 PetscFunctionBegin; 2405 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2406 PetscFunctionReturn(0); 2407 } 2408 2409 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A) 2410 { 2411 PetscErrorCode ierr; 2412 PetscBool sc = PETSC_FALSE,flg; 2413 2414 PetscFunctionBegin; 2415 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2416 ierr = PetscObjectOptionsBegin((PetscObject)A); 2417 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2418 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2419 if (flg) { 2420 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2421 } 2422 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2423 PetscFunctionReturn(0); 2424 } 2425 2426 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2427 { 2428 PetscErrorCode ierr; 2429 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2430 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2431 2432 PetscFunctionBegin; 2433 if (!Y->preallocated) { 2434 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2435 } else if (!aij->nz) { 2436 PetscInt nonew = aij->nonew; 2437 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2438 aij->nonew = nonew; 2439 } 2440 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2441 PetscFunctionReturn(0); 2442 } 2443 2444 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2445 { 2446 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2447 PetscErrorCode ierr; 2448 2449 PetscFunctionBegin; 2450 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2451 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2452 if (d) { 2453 PetscInt rstart; 2454 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2455 *d += rstart; 2456 2457 } 2458 PetscFunctionReturn(0); 2459 } 2460 2461 2462 /* -------------------------------------------------------------------*/ 2463 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2464 MatGetRow_MPIAIJ, 2465 MatRestoreRow_MPIAIJ, 2466 MatMult_MPIAIJ, 2467 /* 4*/ MatMultAdd_MPIAIJ, 2468 MatMultTranspose_MPIAIJ, 2469 MatMultTransposeAdd_MPIAIJ, 2470 0, 2471 0, 2472 0, 2473 /*10*/ 0, 2474 0, 2475 0, 2476 MatSOR_MPIAIJ, 2477 MatTranspose_MPIAIJ, 2478 /*15*/ MatGetInfo_MPIAIJ, 2479 MatEqual_MPIAIJ, 2480 MatGetDiagonal_MPIAIJ, 2481 MatDiagonalScale_MPIAIJ, 2482 MatNorm_MPIAIJ, 2483 /*20*/ MatAssemblyBegin_MPIAIJ, 2484 MatAssemblyEnd_MPIAIJ, 2485 MatSetOption_MPIAIJ, 2486 MatZeroEntries_MPIAIJ, 2487 /*24*/ MatZeroRows_MPIAIJ, 2488 0, 2489 0, 2490 0, 2491 0, 2492 /*29*/ MatSetUp_MPIAIJ, 2493 0, 2494 0, 2495 MatGetDiagonalBlock_MPIAIJ, 2496 0, 2497 /*34*/ MatDuplicate_MPIAIJ, 2498 0, 2499 0, 2500 0, 2501 0, 2502 /*39*/ MatAXPY_MPIAIJ, 2503 MatCreateSubMatrices_MPIAIJ, 2504 MatIncreaseOverlap_MPIAIJ, 2505 MatGetValues_MPIAIJ, 2506 MatCopy_MPIAIJ, 2507 /*44*/ MatGetRowMax_MPIAIJ, 2508 MatScale_MPIAIJ, 2509 MatShift_MPIAIJ, 2510 MatDiagonalSet_MPIAIJ, 2511 MatZeroRowsColumns_MPIAIJ, 2512 /*49*/ MatSetRandom_MPIAIJ, 2513 0, 2514 0, 2515 0, 2516 0, 2517 /*54*/ MatFDColoringCreate_MPIXAIJ, 2518 0, 2519 MatSetUnfactored_MPIAIJ, 2520 MatPermute_MPIAIJ, 2521 0, 2522 /*59*/ MatCreateSubMatrix_MPIAIJ, 2523 MatDestroy_MPIAIJ, 2524 MatView_MPIAIJ, 2525 0, 2526 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2527 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2528 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2529 0, 2530 0, 2531 0, 2532 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2533 MatGetRowMinAbs_MPIAIJ, 2534 0, 2535 0, 2536 0, 2537 0, 2538 /*75*/ MatFDColoringApply_AIJ, 2539 MatSetFromOptions_MPIAIJ, 2540 0, 2541 0, 2542 MatFindZeroDiagonals_MPIAIJ, 2543 /*80*/ 0, 2544 0, 2545 0, 2546 /*83*/ MatLoad_MPIAIJ, 2547 0, 2548 0, 2549 0, 2550 0, 2551 0, 2552 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2553 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2554 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2555 MatPtAP_MPIAIJ_MPIAIJ, 2556 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2557 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2558 0, 2559 0, 2560 0, 2561 0, 2562 /*99*/ 0, 2563 0, 2564 0, 2565 MatConjugate_MPIAIJ, 2566 0, 2567 /*104*/MatSetValuesRow_MPIAIJ, 2568 MatRealPart_MPIAIJ, 2569 MatImaginaryPart_MPIAIJ, 2570 0, 2571 0, 2572 /*109*/0, 2573 0, 2574 MatGetRowMin_MPIAIJ, 2575 0, 2576 MatMissingDiagonal_MPIAIJ, 2577 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2578 0, 2579 MatGetGhosts_MPIAIJ, 2580 0, 2581 0, 2582 /*119*/0, 2583 0, 2584 0, 2585 0, 2586 MatGetMultiProcBlock_MPIAIJ, 2587 /*124*/MatFindNonzeroRows_MPIAIJ, 2588 MatGetColumnNorms_MPIAIJ, 2589 MatInvertBlockDiagonal_MPIAIJ, 2590 0, 2591 MatCreateSubMatricesMPI_MPIAIJ, 2592 /*129*/0, 2593 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2594 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2595 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2596 0, 2597 /*134*/0, 2598 0, 2599 0, 2600 0, 2601 0, 2602 /*139*/MatSetBlockSizes_MPIAIJ, 2603 0, 2604 0, 2605 MatFDColoringSetUp_MPIXAIJ, 2606 MatFindOffBlockDiagonalEntries_MPIAIJ, 2607 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2608 }; 2609 2610 /* ----------------------------------------------------------------------------------------*/ 2611 2612 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2613 { 2614 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2615 PetscErrorCode ierr; 2616 2617 PetscFunctionBegin; 2618 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2619 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2620 PetscFunctionReturn(0); 2621 } 2622 2623 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2624 { 2625 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2626 PetscErrorCode ierr; 2627 2628 PetscFunctionBegin; 2629 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2630 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2631 PetscFunctionReturn(0); 2632 } 2633 2634 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2635 { 2636 Mat_MPIAIJ *b; 2637 PetscErrorCode ierr; 2638 2639 PetscFunctionBegin; 2640 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2641 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2642 b = (Mat_MPIAIJ*)B->data; 2643 2644 #if defined(PETSC_USE_CTABLE) 2645 ierr = PetscTableDestroy(&b->colmap);CHKERRQ(ierr); 2646 #else 2647 ierr = PetscFree(b->colmap);CHKERRQ(ierr); 2648 #endif 2649 ierr = PetscFree(b->garray);CHKERRQ(ierr); 2650 ierr = VecDestroy(&b->lvec);CHKERRQ(ierr); 2651 ierr = VecScatterDestroy(&b->Mvctx);CHKERRQ(ierr); 2652 2653 /* Because the B will have been resized we simply destroy it and create a new one each time */ 2654 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2655 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2656 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2657 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2658 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2659 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2660 2661 if (!B->preallocated) { 2662 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2663 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2664 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2665 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2666 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2667 } 2668 2669 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2670 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2671 B->preallocated = PETSC_TRUE; 2672 B->was_assembled = PETSC_FALSE; 2673 B->assembled = PETSC_FALSE;; 2674 PetscFunctionReturn(0); 2675 } 2676 2677 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2678 { 2679 Mat mat; 2680 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2681 PetscErrorCode ierr; 2682 2683 PetscFunctionBegin; 2684 *newmat = 0; 2685 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2686 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2687 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2688 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2689 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2690 a = (Mat_MPIAIJ*)mat->data; 2691 2692 mat->factortype = matin->factortype; 2693 mat->assembled = PETSC_TRUE; 2694 mat->insertmode = NOT_SET_VALUES; 2695 mat->preallocated = PETSC_TRUE; 2696 2697 a->size = oldmat->size; 2698 a->rank = oldmat->rank; 2699 a->donotstash = oldmat->donotstash; 2700 a->roworiented = oldmat->roworiented; 2701 a->rowindices = 0; 2702 a->rowvalues = 0; 2703 a->getrowactive = PETSC_FALSE; 2704 2705 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2706 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2707 2708 if (oldmat->colmap) { 2709 #if defined(PETSC_USE_CTABLE) 2710 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2711 #else 2712 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2713 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2714 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2715 #endif 2716 } else a->colmap = 0; 2717 if (oldmat->garray) { 2718 PetscInt len; 2719 len = oldmat->B->cmap->n; 2720 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2721 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2722 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2723 } else a->garray = 0; 2724 2725 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2726 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2727 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2728 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2729 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2730 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2731 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2732 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2733 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2734 *newmat = mat; 2735 PetscFunctionReturn(0); 2736 } 2737 2738 2739 2740 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2741 { 2742 PetscScalar *vals,*svals; 2743 MPI_Comm comm; 2744 PetscErrorCode ierr; 2745 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2746 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2747 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2748 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2749 PetscInt cend,cstart,n,*rowners; 2750 int fd; 2751 PetscInt bs = newMat->rmap->bs; 2752 2753 PetscFunctionBegin; 2754 /* force binary viewer to load .info file if it has not yet done so */ 2755 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2756 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2757 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2758 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2759 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2760 if (!rank) { 2761 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2762 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2763 if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ"); 2764 } 2765 2766 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");CHKERRQ(ierr); 2767 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2768 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2769 if (bs < 0) bs = 1; 2770 2771 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2772 M = header[1]; N = header[2]; 2773 2774 /* If global sizes are set, check if they are consistent with that given in the file */ 2775 if (newMat->rmap->N >= 0 && newMat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newMat->rmap->N,M); 2776 if (newMat->cmap->N >=0 && newMat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newMat->cmap->N,N); 2777 2778 /* determine ownership of all (block) rows */ 2779 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2780 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2781 else m = newMat->rmap->n; /* Set by user */ 2782 2783 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2784 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2785 2786 /* First process needs enough room for process with most rows */ 2787 if (!rank) { 2788 mmax = rowners[1]; 2789 for (i=2; i<=size; i++) { 2790 mmax = PetscMax(mmax, rowners[i]); 2791 } 2792 } else mmax = -1; /* unused, but compilers complain */ 2793 2794 rowners[0] = 0; 2795 for (i=2; i<=size; i++) { 2796 rowners[i] += rowners[i-1]; 2797 } 2798 rstart = rowners[rank]; 2799 rend = rowners[rank+1]; 2800 2801 /* distribute row lengths to all processors */ 2802 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2803 if (!rank) { 2804 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2805 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2806 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2807 for (j=0; j<m; j++) { 2808 procsnz[0] += ourlens[j]; 2809 } 2810 for (i=1; i<size; i++) { 2811 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2812 /* calculate the number of nonzeros on each processor */ 2813 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2814 procsnz[i] += rowlengths[j]; 2815 } 2816 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2817 } 2818 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2819 } else { 2820 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2821 } 2822 2823 if (!rank) { 2824 /* determine max buffer needed and allocate it */ 2825 maxnz = 0; 2826 for (i=0; i<size; i++) { 2827 maxnz = PetscMax(maxnz,procsnz[i]); 2828 } 2829 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2830 2831 /* read in my part of the matrix column indices */ 2832 nz = procsnz[0]; 2833 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2834 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2835 2836 /* read in every one elses and ship off */ 2837 for (i=1; i<size; i++) { 2838 nz = procsnz[i]; 2839 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2840 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2841 } 2842 ierr = PetscFree(cols);CHKERRQ(ierr); 2843 } else { 2844 /* determine buffer space needed for message */ 2845 nz = 0; 2846 for (i=0; i<m; i++) { 2847 nz += ourlens[i]; 2848 } 2849 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2850 2851 /* receive message of column indices*/ 2852 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2853 } 2854 2855 /* determine column ownership if matrix is not square */ 2856 if (N != M) { 2857 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2858 else n = newMat->cmap->n; 2859 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2860 cstart = cend - n; 2861 } else { 2862 cstart = rstart; 2863 cend = rend; 2864 n = cend - cstart; 2865 } 2866 2867 /* loop over local rows, determining number of off diagonal entries */ 2868 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2869 jj = 0; 2870 for (i=0; i<m; i++) { 2871 for (j=0; j<ourlens[i]; j++) { 2872 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2873 jj++; 2874 } 2875 } 2876 2877 for (i=0; i<m; i++) { 2878 ourlens[i] -= offlens[i]; 2879 } 2880 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 2881 2882 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 2883 2884 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 2885 2886 for (i=0; i<m; i++) { 2887 ourlens[i] += offlens[i]; 2888 } 2889 2890 if (!rank) { 2891 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 2892 2893 /* read in my part of the matrix numerical values */ 2894 nz = procsnz[0]; 2895 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2896 2897 /* insert into matrix */ 2898 jj = rstart; 2899 smycols = mycols; 2900 svals = vals; 2901 for (i=0; i<m; i++) { 2902 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2903 smycols += ourlens[i]; 2904 svals += ourlens[i]; 2905 jj++; 2906 } 2907 2908 /* read in other processors and ship out */ 2909 for (i=1; i<size; i++) { 2910 nz = procsnz[i]; 2911 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2912 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2913 } 2914 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2915 } else { 2916 /* receive numeric values */ 2917 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 2918 2919 /* receive message of values*/ 2920 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2921 2922 /* insert into matrix */ 2923 jj = rstart; 2924 smycols = mycols; 2925 svals = vals; 2926 for (i=0; i<m; i++) { 2927 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2928 smycols += ourlens[i]; 2929 svals += ourlens[i]; 2930 jj++; 2931 } 2932 } 2933 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2934 ierr = PetscFree(vals);CHKERRQ(ierr); 2935 ierr = PetscFree(mycols);CHKERRQ(ierr); 2936 ierr = PetscFree(rowners);CHKERRQ(ierr); 2937 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2938 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2939 PetscFunctionReturn(0); 2940 } 2941 2942 /* TODO: Not scalable because of ISAllGather() unless getting all columns. */ 2943 PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2944 { 2945 PetscErrorCode ierr; 2946 IS iscol_local; 2947 PetscInt csize; 2948 2949 PetscFunctionBegin; 2950 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2951 if (call == MAT_REUSE_MATRIX) { 2952 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2953 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2954 } else { 2955 /* check if we are grabbing all columns*/ 2956 PetscBool isstride; 2957 PetscMPIInt lisstride = 0,gisstride; 2958 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 2959 if (isstride) { 2960 PetscInt start,len,mstart,mlen; 2961 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 2962 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 2963 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 2964 if (mstart == start && mlen-mstart == len) lisstride = 1; 2965 } 2966 ierr = MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2967 if (gisstride) { 2968 PetscInt N; 2969 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 2970 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 2971 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 2972 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 2973 } else { 2974 PetscInt cbs; 2975 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2976 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2977 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 2978 } 2979 } 2980 2981 ierr = MatCreateSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2982 if (call == MAT_INITIAL_MATRIX) { 2983 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2984 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2985 } 2986 PetscFunctionReturn(0); 2987 } 2988 2989 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat*); 2990 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*); 2991 2992 PetscErrorCode MatCreateSubMatrix_MPIAIJ_Private_SameDist(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2993 { 2994 PetscErrorCode ierr; 2995 PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs; 2996 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 2997 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 2998 Mat M,Msub,B=a->B; 2999 MatScalar *aa; 3000 Mat_SeqAIJ *aij; 3001 PetscInt *garray = a->garray,*colsub; 3002 PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend; 3003 IS iscol_sub,iscmap; 3004 const PetscInt *is_idx,*cmap; 3005 3006 PetscFunctionBegin; 3007 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); /* iscol should be sequential */ 3008 3009 if (call == MAT_INITIAL_MATRIX) { 3010 /* create scalable iscol_sub (a subset of iscol) */ 3011 PetscInt *idx,*cmap1; 3012 3013 ierr = PetscMalloc2(n,&idx,n,&cmap1);CHKERRQ(ierr); 3014 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3015 count = 0; 3016 3017 /* A part */ 3018 j = cstart; 3019 for (i=0; i<n; i++) { 3020 if (j >= cend) break; 3021 if (is_idx[i] == j) { 3022 idx[count] = j; 3023 cmap1[count] = i; /* column index in submat */ 3024 count++; j++; 3025 } else if (is_idx[i] > j) { 3026 while (is_idx[i] > j && j < cend-1) j++; 3027 if (is_idx[i] == j) { 3028 idx[count] = j; 3029 cmap1[count] = i; /* column index in submat */ 3030 count++; j++; 3031 } 3032 } 3033 } 3034 3035 /* B part */ 3036 j = 0; 3037 for (i=0; i<n; i++) { 3038 if (j >= Bn) break; 3039 if (is_idx[i] == garray[j]) { 3040 idx[count] = garray[j]; 3041 cmap1[count] = i; /* column index in submat */ 3042 count++; j++; 3043 } else if (is_idx[i] > garray[j]) { 3044 while (is_idx[i] > garray[j] && j < Bn-1) j++; 3045 if (is_idx[i] == garray[j]) { 3046 idx[count] = garray[j]; 3047 cmap1[count] = i; /* column index in submat */ 3048 count++; j++; 3049 } 3050 } 3051 } 3052 ierr = PetscSortInt(count,cmap1);CHKERRQ(ierr); 3053 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3054 3055 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol),count,idx,PETSC_COPY_VALUES,&iscol_sub);CHKERRQ(ierr); 3056 ierr = ISSort(iscol_sub);CHKERRQ(ierr); 3057 3058 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol),count,cmap1,PETSC_COPY_VALUES,&iscmap);CHKERRQ(ierr); 3059 ierr = PetscFree2(idx,cmap1);CHKERRQ(ierr); 3060 3061 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3062 3063 } else { /* call == MAT_REUSE_MATRIX */ 3064 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);CHKERRQ(ierr); 3065 if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse"); 3066 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3067 3068 ierr = PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);CHKERRQ(ierr); 3069 if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse"); 3070 3071 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);CHKERRQ(ierr); 3072 if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3073 3074 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3075 } 3076 3077 aij = (Mat_SeqAIJ*)(Msub)->data; 3078 ii = aij->i; 3079 ierr = ISGetIndices(iscmap,&cmap);CHKERRQ(ierr); 3080 3081 /* 3082 m - number of local rows 3083 n - number of columns (same on all processors) 3084 rstart - first row in new global matrix generated 3085 */ 3086 ierr = MatGetSize(Msub,&m,NULL);CHKERRQ(ierr); 3087 3088 if (call == MAT_INITIAL_MATRIX) { 3089 MPI_Comm comm; 3090 PetscMPIInt rank,size; 3091 3092 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3093 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3094 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3095 3096 /* 3097 Determine the number of non-zeros in the diagonal and off-diagonal 3098 portions of the matrix in order to do correct preallocation 3099 */ 3100 3101 /* first get start and end of "diagonal" columns */ 3102 if (csize == PETSC_DECIDE) { 3103 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3104 if (mglobal == n) { /* square matrix */ 3105 nlocal = m; 3106 } else { 3107 nlocal = n/size + ((n % size) > rank); 3108 } 3109 } else { 3110 nlocal = csize; 3111 } 3112 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3113 rstart = rend - nlocal; 3114 if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 3115 3116 /* next, compute all the lengths */ 3117 jj = aij->j; 3118 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3119 olens = dlens + m; 3120 for (i=0; i<m; i++) { 3121 jend = ii[i+1] - ii[i]; 3122 olen = 0; 3123 dlen = 0; 3124 for (j=0; j<jend; j++) { 3125 if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++; 3126 else dlen++; 3127 jj++; 3128 } 3129 olens[i] = olen; 3130 dlens[i] = dlen; 3131 } 3132 ierr = MatGetBlockSizes(Msub,&bs,&cbs);CHKERRQ(ierr); 3133 3134 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3135 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3136 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3137 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3138 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3139 ierr = PetscFree(dlens);CHKERRQ(ierr); 3140 } else { 3141 M = *newmat; 3142 ierr = MatGetLocalSize(M,&i,NULL);CHKERRQ(ierr); 3143 if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3144 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3145 /* 3146 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3147 rather than the slower MatSetValues(). 3148 */ 3149 M->was_assembled = PETSC_TRUE; 3150 M->assembled = PETSC_FALSE; 3151 } 3152 3153 /* set values of Msub to *newmat */ 3154 ierr = PetscMalloc1(count,&colsub);CHKERRQ(ierr); 3155 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 3156 3157 jj = aij->j; 3158 aa = aij->a; 3159 for (i=0; i<m; i++) { 3160 row = rstart + i; 3161 nz = ii[i+1] - ii[i]; 3162 for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]]; 3163 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);CHKERRQ(ierr); 3164 jj += nz; aa += nz; 3165 } 3166 ierr = ISRestoreIndices(iscmap,&cmap);CHKERRQ(ierr); 3167 3168 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3169 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3170 *newmat = M; 3171 3172 ierr = PetscFree(colsub);CHKERRQ(ierr); 3173 3174 /* save Msub, iscol_sub and iscmap used in processor for next request */ 3175 if (call == MAT_INITIAL_MATRIX) { 3176 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Msub);CHKERRQ(ierr); 3177 ierr = MatDestroy(&Msub);CHKERRQ(ierr); 3178 3179 ierr = PetscObjectCompose((PetscObject)M,"SubIScol",(PetscObject)iscol_sub);CHKERRQ(ierr); 3180 ierr = ISDestroy(&iscol_sub);CHKERRQ(ierr); 3181 3182 ierr = PetscObjectCompose((PetscObject)M,"Subcmap",(PetscObject)iscmap);CHKERRQ(ierr); 3183 ierr = ISDestroy(&iscmap);CHKERRQ(ierr); 3184 } 3185 PetscFunctionReturn(0); 3186 } 3187 3188 /* 3189 Not great since it makes two copies of the submatrix, first an SeqAIJ 3190 in local and then by concatenating the local matrices the end result. 3191 Writing it directly would be much like MatCreateSubMatrices_MPIAIJ() 3192 3193 Note: This requires a sequential iscol with all indices. 3194 */ 3195 PetscErrorCode MatCreateSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3196 { 3197 PetscErrorCode ierr; 3198 PetscMPIInt rank,size; 3199 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3200 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3201 Mat M,Mreuse; 3202 MatScalar *aa,*vwork; 3203 MPI_Comm comm; 3204 Mat_SeqAIJ *aij; 3205 PetscBool sameDist=PETSC_FALSE,tsameDist; 3206 3207 PetscFunctionBegin; 3208 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3209 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3210 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3211 3212 /* If isrow has same processor distribution as mat, then use a scalable routine */ 3213 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3214 if (!n) { 3215 sameDist=PETSC_TRUE; 3216 } else { 3217 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3218 ierr = MatGetOwnershipRange(mat,&rstart,&rend);CHKERRQ(ierr); 3219 if (i >= rstart && j < rend) sameDist=PETSC_TRUE; 3220 } 3221 ierr = MPIU_Allreduce(&sameDist,&tsameDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3222 if (tsameDist) { 3223 ierr = MatCreateSubMatrix_MPIAIJ_Private_SameDist(mat,isrow,iscol,csize,call,newmat);CHKERRQ(ierr); 3224 PetscFunctionReturn(0); 3225 } 3226 3227 if (call == MAT_REUSE_MATRIX) { 3228 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3229 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3230 ierr = MatCreateSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&Mreuse);CHKERRQ(ierr); 3231 } else { 3232 ierr = MatCreateSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&Mreuse);CHKERRQ(ierr); 3233 } 3234 3235 /* 3236 m - number of local rows 3237 n - number of columns (same on all processors) 3238 rstart - first row in new global matrix generated 3239 */ 3240 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3241 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3242 if (call == MAT_INITIAL_MATRIX) { 3243 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3244 ii = aij->i; 3245 jj = aij->j; 3246 3247 /* 3248 Determine the number of non-zeros in the diagonal and off-diagonal 3249 portions of the matrix in order to do correct preallocation 3250 */ 3251 3252 /* first get start and end of "diagonal" columns */ 3253 if (csize == PETSC_DECIDE) { 3254 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3255 if (mglobal == n) { /* square matrix */ 3256 nlocal = m; 3257 } else { 3258 nlocal = n/size + ((n % size) > rank); 3259 } 3260 } else { 3261 nlocal = csize; 3262 } 3263 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3264 rstart = rend - nlocal; 3265 if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 3266 3267 /* next, compute all the lengths */ 3268 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3269 olens = dlens + m; 3270 for (i=0; i<m; i++) { 3271 jend = ii[i+1] - ii[i]; 3272 olen = 0; 3273 dlen = 0; 3274 for (j=0; j<jend; j++) { 3275 if (*jj < rstart || *jj >= rend) olen++; 3276 else dlen++; 3277 jj++; 3278 } 3279 olens[i] = olen; 3280 dlens[i] = dlen; 3281 } 3282 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3283 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3284 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3285 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3286 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3287 ierr = PetscFree(dlens);CHKERRQ(ierr); 3288 } else { 3289 PetscInt ml,nl; 3290 3291 M = *newmat; 3292 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3293 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3294 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3295 /* 3296 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3297 rather than the slower MatSetValues(). 3298 */ 3299 M->was_assembled = PETSC_TRUE; 3300 M->assembled = PETSC_FALSE; 3301 } 3302 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3303 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3304 ii = aij->i; 3305 jj = aij->j; 3306 aa = aij->a; 3307 for (i=0; i<m; i++) { 3308 row = rstart + i; 3309 nz = ii[i+1] - ii[i]; 3310 cwork = jj; jj += nz; 3311 vwork = aa; aa += nz; 3312 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3313 } 3314 3315 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3316 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3317 *newmat = M; 3318 3319 /* save submatrix used in processor for next request */ 3320 if (call == MAT_INITIAL_MATRIX) { 3321 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3322 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3323 } 3324 PetscFunctionReturn(0); 3325 } 3326 3327 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3328 { 3329 PetscInt m,cstart, cend,j,nnz,i,d; 3330 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3331 const PetscInt *JJ; 3332 PetscScalar *values; 3333 PetscErrorCode ierr; 3334 PetscBool nooffprocentries; 3335 3336 PetscFunctionBegin; 3337 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3338 3339 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3340 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3341 m = B->rmap->n; 3342 cstart = B->cmap->rstart; 3343 cend = B->cmap->rend; 3344 rstart = B->rmap->rstart; 3345 3346 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3347 3348 #if defined(PETSC_USE_DEBUGGING) 3349 for (i=0; i<m; i++) { 3350 nnz = Ii[i+1]- Ii[i]; 3351 JJ = J + Ii[i]; 3352 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3353 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3354 if (nnz && (JJ[nnz-1] >= B->cmap->N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N); 3355 } 3356 #endif 3357 3358 for (i=0; i<m; i++) { 3359 nnz = Ii[i+1]- Ii[i]; 3360 JJ = J + Ii[i]; 3361 nnz_max = PetscMax(nnz_max,nnz); 3362 d = 0; 3363 for (j=0; j<nnz; j++) { 3364 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3365 } 3366 d_nnz[i] = d; 3367 o_nnz[i] = nnz - d; 3368 } 3369 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3370 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3371 3372 if (v) values = (PetscScalar*)v; 3373 else { 3374 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3375 } 3376 3377 for (i=0; i<m; i++) { 3378 ii = i + rstart; 3379 nnz = Ii[i+1]- Ii[i]; 3380 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3381 } 3382 nooffprocentries = B->nooffprocentries; 3383 B->nooffprocentries = PETSC_TRUE; 3384 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3385 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3386 B->nooffprocentries = nooffprocentries; 3387 3388 if (!v) { 3389 ierr = PetscFree(values);CHKERRQ(ierr); 3390 } 3391 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3392 PetscFunctionReturn(0); 3393 } 3394 3395 /*@ 3396 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3397 (the default parallel PETSc format). 3398 3399 Collective on MPI_Comm 3400 3401 Input Parameters: 3402 + B - the matrix 3403 . i - the indices into j for the start of each local row (starts with zero) 3404 . j - the column indices for each local row (starts with zero) 3405 - v - optional values in the matrix 3406 3407 Level: developer 3408 3409 Notes: 3410 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3411 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3412 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3413 3414 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3415 3416 The format which is used for the sparse matrix input, is equivalent to a 3417 row-major ordering.. i.e for the following matrix, the input data expected is 3418 as shown 3419 3420 $ 1 0 0 3421 $ 2 0 3 P0 3422 $ ------- 3423 $ 4 5 6 P1 3424 $ 3425 $ Process0 [P0]: rows_owned=[0,1] 3426 $ i = {0,1,3} [size = nrow+1 = 2+1] 3427 $ j = {0,0,2} [size = 3] 3428 $ v = {1,2,3} [size = 3] 3429 $ 3430 $ Process1 [P1]: rows_owned=[2] 3431 $ i = {0,3} [size = nrow+1 = 1+1] 3432 $ j = {0,1,2} [size = 3] 3433 $ v = {4,5,6} [size = 3] 3434 3435 .keywords: matrix, aij, compressed row, sparse, parallel 3436 3437 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ, 3438 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3439 @*/ 3440 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3441 { 3442 PetscErrorCode ierr; 3443 3444 PetscFunctionBegin; 3445 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3446 PetscFunctionReturn(0); 3447 } 3448 3449 /*@C 3450 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3451 (the default parallel PETSc format). For good matrix assembly performance 3452 the user should preallocate the matrix storage by setting the parameters 3453 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3454 performance can be increased by more than a factor of 50. 3455 3456 Collective on MPI_Comm 3457 3458 Input Parameters: 3459 + B - the matrix 3460 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3461 (same value is used for all local rows) 3462 . d_nnz - array containing the number of nonzeros in the various rows of the 3463 DIAGONAL portion of the local submatrix (possibly different for each row) 3464 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3465 The size of this array is equal to the number of local rows, i.e 'm'. 3466 For matrices that will be factored, you must leave room for (and set) 3467 the diagonal entry even if it is zero. 3468 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3469 submatrix (same value is used for all local rows). 3470 - o_nnz - array containing the number of nonzeros in the various rows of the 3471 OFF-DIAGONAL portion of the local submatrix (possibly different for 3472 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3473 structure. The size of this array is equal to the number 3474 of local rows, i.e 'm'. 3475 3476 If the *_nnz parameter is given then the *_nz parameter is ignored 3477 3478 The AIJ format (also called the Yale sparse matrix format or 3479 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3480 storage. The stored row and column indices begin with zero. 3481 See Users-Manual: ch_mat for details. 3482 3483 The parallel matrix is partitioned such that the first m0 rows belong to 3484 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3485 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3486 3487 The DIAGONAL portion of the local submatrix of a processor can be defined 3488 as the submatrix which is obtained by extraction the part corresponding to 3489 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3490 first row that belongs to the processor, r2 is the last row belonging to 3491 the this processor, and c1-c2 is range of indices of the local part of a 3492 vector suitable for applying the matrix to. This is an mxn matrix. In the 3493 common case of a square matrix, the row and column ranges are the same and 3494 the DIAGONAL part is also square. The remaining portion of the local 3495 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3496 3497 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3498 3499 You can call MatGetInfo() to get information on how effective the preallocation was; 3500 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3501 You can also run with the option -info and look for messages with the string 3502 malloc in them to see if additional memory allocation was needed. 3503 3504 Example usage: 3505 3506 Consider the following 8x8 matrix with 34 non-zero values, that is 3507 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3508 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3509 as follows: 3510 3511 .vb 3512 1 2 0 | 0 3 0 | 0 4 3513 Proc0 0 5 6 | 7 0 0 | 8 0 3514 9 0 10 | 11 0 0 | 12 0 3515 ------------------------------------- 3516 13 0 14 | 15 16 17 | 0 0 3517 Proc1 0 18 0 | 19 20 21 | 0 0 3518 0 0 0 | 22 23 0 | 24 0 3519 ------------------------------------- 3520 Proc2 25 26 27 | 0 0 28 | 29 0 3521 30 0 0 | 31 32 33 | 0 34 3522 .ve 3523 3524 This can be represented as a collection of submatrices as: 3525 3526 .vb 3527 A B C 3528 D E F 3529 G H I 3530 .ve 3531 3532 Where the submatrices A,B,C are owned by proc0, D,E,F are 3533 owned by proc1, G,H,I are owned by proc2. 3534 3535 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3536 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3537 The 'M','N' parameters are 8,8, and have the same values on all procs. 3538 3539 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3540 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3541 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3542 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3543 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3544 matrix, ans [DF] as another SeqAIJ matrix. 3545 3546 When d_nz, o_nz parameters are specified, d_nz storage elements are 3547 allocated for every row of the local diagonal submatrix, and o_nz 3548 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3549 One way to choose d_nz and o_nz is to use the max nonzerors per local 3550 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3551 In this case, the values of d_nz,o_nz are: 3552 .vb 3553 proc0 : dnz = 2, o_nz = 2 3554 proc1 : dnz = 3, o_nz = 2 3555 proc2 : dnz = 1, o_nz = 4 3556 .ve 3557 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3558 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3559 for proc3. i.e we are using 12+15+10=37 storage locations to store 3560 34 values. 3561 3562 When d_nnz, o_nnz parameters are specified, the storage is specified 3563 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3564 In the above case the values for d_nnz,o_nnz are: 3565 .vb 3566 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3567 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3568 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3569 .ve 3570 Here the space allocated is sum of all the above values i.e 34, and 3571 hence pre-allocation is perfect. 3572 3573 Level: intermediate 3574 3575 .keywords: matrix, aij, compressed row, sparse, parallel 3576 3577 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3578 MATMPIAIJ, MatGetInfo(), PetscSplitOwnership() 3579 @*/ 3580 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3581 { 3582 PetscErrorCode ierr; 3583 3584 PetscFunctionBegin; 3585 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3586 PetscValidType(B,1); 3587 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3588 PetscFunctionReturn(0); 3589 } 3590 3591 /*@ 3592 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3593 CSR format the local rows. 3594 3595 Collective on MPI_Comm 3596 3597 Input Parameters: 3598 + comm - MPI communicator 3599 . m - number of local rows (Cannot be PETSC_DECIDE) 3600 . n - This value should be the same as the local size used in creating the 3601 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3602 calculated if N is given) For square matrices n is almost always m. 3603 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3604 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3605 . i - row indices 3606 . j - column indices 3607 - a - matrix values 3608 3609 Output Parameter: 3610 . mat - the matrix 3611 3612 Level: intermediate 3613 3614 Notes: 3615 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3616 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3617 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3618 3619 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3620 3621 The format which is used for the sparse matrix input, is equivalent to a 3622 row-major ordering.. i.e for the following matrix, the input data expected is 3623 as shown 3624 3625 $ 1 0 0 3626 $ 2 0 3 P0 3627 $ ------- 3628 $ 4 5 6 P1 3629 $ 3630 $ Process0 [P0]: rows_owned=[0,1] 3631 $ i = {0,1,3} [size = nrow+1 = 2+1] 3632 $ j = {0,0,2} [size = 3] 3633 $ v = {1,2,3} [size = 3] 3634 $ 3635 $ Process1 [P1]: rows_owned=[2] 3636 $ i = {0,3} [size = nrow+1 = 1+1] 3637 $ j = {0,1,2} [size = 3] 3638 $ v = {4,5,6} [size = 3] 3639 3640 .keywords: matrix, aij, compressed row, sparse, parallel 3641 3642 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3643 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3644 @*/ 3645 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3646 { 3647 PetscErrorCode ierr; 3648 3649 PetscFunctionBegin; 3650 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3651 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3652 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3653 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3654 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3655 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3656 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3657 PetscFunctionReturn(0); 3658 } 3659 3660 /*@C 3661 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3662 (the default parallel PETSc format). For good matrix assembly performance 3663 the user should preallocate the matrix storage by setting the parameters 3664 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3665 performance can be increased by more than a factor of 50. 3666 3667 Collective on MPI_Comm 3668 3669 Input Parameters: 3670 + comm - MPI communicator 3671 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3672 This value should be the same as the local size used in creating the 3673 y vector for the matrix-vector product y = Ax. 3674 . n - This value should be the same as the local size used in creating the 3675 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3676 calculated if N is given) For square matrices n is almost always m. 3677 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3678 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3679 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3680 (same value is used for all local rows) 3681 . d_nnz - array containing the number of nonzeros in the various rows of the 3682 DIAGONAL portion of the local submatrix (possibly different for each row) 3683 or NULL, if d_nz is used to specify the nonzero structure. 3684 The size of this array is equal to the number of local rows, i.e 'm'. 3685 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3686 submatrix (same value is used for all local rows). 3687 - o_nnz - array containing the number of nonzeros in the various rows of the 3688 OFF-DIAGONAL portion of the local submatrix (possibly different for 3689 each row) or NULL, if o_nz is used to specify the nonzero 3690 structure. The size of this array is equal to the number 3691 of local rows, i.e 'm'. 3692 3693 Output Parameter: 3694 . A - the matrix 3695 3696 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3697 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3698 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3699 3700 Notes: 3701 If the *_nnz parameter is given then the *_nz parameter is ignored 3702 3703 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3704 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3705 storage requirements for this matrix. 3706 3707 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3708 processor than it must be used on all processors that share the object for 3709 that argument. 3710 3711 The user MUST specify either the local or global matrix dimensions 3712 (possibly both). 3713 3714 The parallel matrix is partitioned across processors such that the 3715 first m0 rows belong to process 0, the next m1 rows belong to 3716 process 1, the next m2 rows belong to process 2 etc.. where 3717 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3718 values corresponding to [m x N] submatrix. 3719 3720 The columns are logically partitioned with the n0 columns belonging 3721 to 0th partition, the next n1 columns belonging to the next 3722 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3723 3724 The DIAGONAL portion of the local submatrix on any given processor 3725 is the submatrix corresponding to the rows and columns m,n 3726 corresponding to the given processor. i.e diagonal matrix on 3727 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3728 etc. The remaining portion of the local submatrix [m x (N-n)] 3729 constitute the OFF-DIAGONAL portion. The example below better 3730 illustrates this concept. 3731 3732 For a square global matrix we define each processor's diagonal portion 3733 to be its local rows and the corresponding columns (a square submatrix); 3734 each processor's off-diagonal portion encompasses the remainder of the 3735 local matrix (a rectangular submatrix). 3736 3737 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3738 3739 When calling this routine with a single process communicator, a matrix of 3740 type SEQAIJ is returned. If a matrix of type MATMPIAIJ is desired for this 3741 type of communicator, use the construction mechanism: 3742 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3743 3744 By default, this format uses inodes (identical nodes) when possible. 3745 We search for consecutive rows with the same nonzero structure, thereby 3746 reusing matrix information to achieve increased efficiency. 3747 3748 Options Database Keys: 3749 + -mat_no_inode - Do not use inodes 3750 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3751 - -mat_aij_oneindex - Internally use indexing starting at 1 3752 rather than 0. Note that when calling MatSetValues(), 3753 the user still MUST index entries starting at 0! 3754 3755 3756 Example usage: 3757 3758 Consider the following 8x8 matrix with 34 non-zero values, that is 3759 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3760 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3761 as follows: 3762 3763 .vb 3764 1 2 0 | 0 3 0 | 0 4 3765 Proc0 0 5 6 | 7 0 0 | 8 0 3766 9 0 10 | 11 0 0 | 12 0 3767 ------------------------------------- 3768 13 0 14 | 15 16 17 | 0 0 3769 Proc1 0 18 0 | 19 20 21 | 0 0 3770 0 0 0 | 22 23 0 | 24 0 3771 ------------------------------------- 3772 Proc2 25 26 27 | 0 0 28 | 29 0 3773 30 0 0 | 31 32 33 | 0 34 3774 .ve 3775 3776 This can be represented as a collection of submatrices as: 3777 3778 .vb 3779 A B C 3780 D E F 3781 G H I 3782 .ve 3783 3784 Where the submatrices A,B,C are owned by proc0, D,E,F are 3785 owned by proc1, G,H,I are owned by proc2. 3786 3787 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3788 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3789 The 'M','N' parameters are 8,8, and have the same values on all procs. 3790 3791 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3792 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3793 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3794 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3795 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3796 matrix, ans [DF] as another SeqAIJ matrix. 3797 3798 When d_nz, o_nz parameters are specified, d_nz storage elements are 3799 allocated for every row of the local diagonal submatrix, and o_nz 3800 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3801 One way to choose d_nz and o_nz is to use the max nonzerors per local 3802 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3803 In this case, the values of d_nz,o_nz are: 3804 .vb 3805 proc0 : dnz = 2, o_nz = 2 3806 proc1 : dnz = 3, o_nz = 2 3807 proc2 : dnz = 1, o_nz = 4 3808 .ve 3809 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3810 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3811 for proc3. i.e we are using 12+15+10=37 storage locations to store 3812 34 values. 3813 3814 When d_nnz, o_nnz parameters are specified, the storage is specified 3815 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3816 In the above case the values for d_nnz,o_nnz are: 3817 .vb 3818 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3819 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3820 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3821 .ve 3822 Here the space allocated is sum of all the above values i.e 34, and 3823 hence pre-allocation is perfect. 3824 3825 Level: intermediate 3826 3827 .keywords: matrix, aij, compressed row, sparse, parallel 3828 3829 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3830 MATMPIAIJ, MatCreateMPIAIJWithArrays() 3831 @*/ 3832 PetscErrorCode MatCreateAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 3833 { 3834 PetscErrorCode ierr; 3835 PetscMPIInt size; 3836 3837 PetscFunctionBegin; 3838 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3839 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3840 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3841 if (size > 1) { 3842 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3843 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3844 } else { 3845 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3846 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3847 } 3848 PetscFunctionReturn(0); 3849 } 3850 3851 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3852 { 3853 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3854 PetscBool flg; 3855 PetscErrorCode ierr; 3856 3857 PetscFunctionBegin; 3858 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 3859 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input"); 3860 if (Ad) *Ad = a->A; 3861 if (Ao) *Ao = a->B; 3862 if (colmap) *colmap = a->garray; 3863 PetscFunctionReturn(0); 3864 } 3865 3866 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3867 { 3868 PetscErrorCode ierr; 3869 PetscInt m,N,i,rstart,nnz,Ii; 3870 PetscInt *indx; 3871 PetscScalar *values; 3872 3873 PetscFunctionBegin; 3874 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3875 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3876 PetscInt *dnz,*onz,sum,bs,cbs; 3877 3878 if (n == PETSC_DECIDE) { 3879 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3880 } 3881 /* Check sum(n) = N */ 3882 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3883 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3884 3885 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3886 rstart -= m; 3887 3888 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3889 for (i=0; i<m; i++) { 3890 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3891 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3892 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3893 } 3894 3895 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3896 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3897 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3898 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3899 ierr = MatSetType(*outmat,MATAIJ);CHKERRQ(ierr); 3900 ierr = MatSeqAIJSetPreallocation(*outmat,0,dnz);CHKERRQ(ierr); 3901 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3902 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3903 } 3904 3905 /* numeric phase */ 3906 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3907 for (i=0; i<m; i++) { 3908 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3909 Ii = i + rstart; 3910 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3911 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3912 } 3913 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3914 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3915 PetscFunctionReturn(0); 3916 } 3917 3918 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3919 { 3920 PetscErrorCode ierr; 3921 PetscMPIInt rank; 3922 PetscInt m,N,i,rstart,nnz; 3923 size_t len; 3924 const PetscInt *indx; 3925 PetscViewer out; 3926 char *name; 3927 Mat B; 3928 const PetscScalar *values; 3929 3930 PetscFunctionBegin; 3931 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3932 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3933 /* Should this be the type of the diagonal block of A? */ 3934 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3935 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3936 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3937 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3938 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3939 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3940 for (i=0; i<m; i++) { 3941 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3942 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3943 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3944 } 3945 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3946 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3947 3948 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3949 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3950 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 3951 sprintf(name,"%s.%d",outfile,rank); 3952 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3953 ierr = PetscFree(name);CHKERRQ(ierr); 3954 ierr = MatView(B,out);CHKERRQ(ierr); 3955 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3956 ierr = MatDestroy(&B);CHKERRQ(ierr); 3957 PetscFunctionReturn(0); 3958 } 3959 3960 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3961 { 3962 PetscErrorCode ierr; 3963 Mat_Merge_SeqsToMPI *merge; 3964 PetscContainer container; 3965 3966 PetscFunctionBegin; 3967 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3968 if (container) { 3969 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3970 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3971 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3972 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3973 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3974 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3975 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 3976 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3977 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 3978 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3979 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3980 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3981 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3982 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 3983 ierr = PetscFree(merge);CHKERRQ(ierr); 3984 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3985 } 3986 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3987 PetscFunctionReturn(0); 3988 } 3989 3990 #include <../src/mat/utils/freespace.h> 3991 #include <petscbt.h> 3992 3993 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 3994 { 3995 PetscErrorCode ierr; 3996 MPI_Comm comm; 3997 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 3998 PetscMPIInt size,rank,taga,*len_s; 3999 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4000 PetscInt proc,m; 4001 PetscInt **buf_ri,**buf_rj; 4002 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4003 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4004 MPI_Request *s_waits,*r_waits; 4005 MPI_Status *status; 4006 MatScalar *aa=a->a; 4007 MatScalar **abuf_r,*ba_i; 4008 Mat_Merge_SeqsToMPI *merge; 4009 PetscContainer container; 4010 4011 PetscFunctionBegin; 4012 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4013 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4014 4015 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4016 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4017 4018 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4019 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4020 4021 bi = merge->bi; 4022 bj = merge->bj; 4023 buf_ri = merge->buf_ri; 4024 buf_rj = merge->buf_rj; 4025 4026 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4027 owners = merge->rowmap->range; 4028 len_s = merge->len_s; 4029 4030 /* send and recv matrix values */ 4031 /*-----------------------------*/ 4032 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4033 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4034 4035 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4036 for (proc=0,k=0; proc<size; proc++) { 4037 if (!len_s[proc]) continue; 4038 i = owners[proc]; 4039 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4040 k++; 4041 } 4042 4043 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4044 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4045 ierr = PetscFree(status);CHKERRQ(ierr); 4046 4047 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4048 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4049 4050 /* insert mat values of mpimat */ 4051 /*----------------------------*/ 4052 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4053 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4054 4055 for (k=0; k<merge->nrecv; k++) { 4056 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4057 nrows = *(buf_ri_k[k]); 4058 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4059 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4060 } 4061 4062 /* set values of ba */ 4063 m = merge->rowmap->n; 4064 for (i=0; i<m; i++) { 4065 arow = owners[rank] + i; 4066 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4067 bnzi = bi[i+1] - bi[i]; 4068 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4069 4070 /* add local non-zero vals of this proc's seqmat into ba */ 4071 anzi = ai[arow+1] - ai[arow]; 4072 aj = a->j + ai[arow]; 4073 aa = a->a + ai[arow]; 4074 nextaj = 0; 4075 for (j=0; nextaj<anzi; j++) { 4076 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4077 ba_i[j] += aa[nextaj++]; 4078 } 4079 } 4080 4081 /* add received vals into ba */ 4082 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4083 /* i-th row */ 4084 if (i == *nextrow[k]) { 4085 anzi = *(nextai[k]+1) - *nextai[k]; 4086 aj = buf_rj[k] + *(nextai[k]); 4087 aa = abuf_r[k] + *(nextai[k]); 4088 nextaj = 0; 4089 for (j=0; nextaj<anzi; j++) { 4090 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4091 ba_i[j] += aa[nextaj++]; 4092 } 4093 } 4094 nextrow[k]++; nextai[k]++; 4095 } 4096 } 4097 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4098 } 4099 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4100 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4101 4102 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4103 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4104 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4105 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4106 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4107 PetscFunctionReturn(0); 4108 } 4109 4110 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4111 { 4112 PetscErrorCode ierr; 4113 Mat B_mpi; 4114 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4115 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4116 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4117 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4118 PetscInt len,proc,*dnz,*onz,bs,cbs; 4119 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4120 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4121 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4122 MPI_Status *status; 4123 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4124 PetscBT lnkbt; 4125 Mat_Merge_SeqsToMPI *merge; 4126 PetscContainer container; 4127 4128 PetscFunctionBegin; 4129 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4130 4131 /* make sure it is a PETSc comm */ 4132 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4133 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4134 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4135 4136 ierr = PetscNew(&merge);CHKERRQ(ierr); 4137 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4138 4139 /* determine row ownership */ 4140 /*---------------------------------------------------------*/ 4141 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4142 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4143 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4144 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4145 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4146 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4147 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4148 4149 m = merge->rowmap->n; 4150 owners = merge->rowmap->range; 4151 4152 /* determine the number of messages to send, their lengths */ 4153 /*---------------------------------------------------------*/ 4154 len_s = merge->len_s; 4155 4156 len = 0; /* length of buf_si[] */ 4157 merge->nsend = 0; 4158 for (proc=0; proc<size; proc++) { 4159 len_si[proc] = 0; 4160 if (proc == rank) { 4161 len_s[proc] = 0; 4162 } else { 4163 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4164 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4165 } 4166 if (len_s[proc]) { 4167 merge->nsend++; 4168 nrows = 0; 4169 for (i=owners[proc]; i<owners[proc+1]; i++) { 4170 if (ai[i+1] > ai[i]) nrows++; 4171 } 4172 len_si[proc] = 2*(nrows+1); 4173 len += len_si[proc]; 4174 } 4175 } 4176 4177 /* determine the number and length of messages to receive for ij-structure */ 4178 /*-------------------------------------------------------------------------*/ 4179 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4180 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4181 4182 /* post the Irecv of j-structure */ 4183 /*-------------------------------*/ 4184 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4185 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4186 4187 /* post the Isend of j-structure */ 4188 /*--------------------------------*/ 4189 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4190 4191 for (proc=0, k=0; proc<size; proc++) { 4192 if (!len_s[proc]) continue; 4193 i = owners[proc]; 4194 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4195 k++; 4196 } 4197 4198 /* receives and sends of j-structure are complete */ 4199 /*------------------------------------------------*/ 4200 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4201 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4202 4203 /* send and recv i-structure */ 4204 /*---------------------------*/ 4205 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4206 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4207 4208 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4209 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4210 for (proc=0,k=0; proc<size; proc++) { 4211 if (!len_s[proc]) continue; 4212 /* form outgoing message for i-structure: 4213 buf_si[0]: nrows to be sent 4214 [1:nrows]: row index (global) 4215 [nrows+1:2*nrows+1]: i-structure index 4216 */ 4217 /*-------------------------------------------*/ 4218 nrows = len_si[proc]/2 - 1; 4219 buf_si_i = buf_si + nrows+1; 4220 buf_si[0] = nrows; 4221 buf_si_i[0] = 0; 4222 nrows = 0; 4223 for (i=owners[proc]; i<owners[proc+1]; i++) { 4224 anzi = ai[i+1] - ai[i]; 4225 if (anzi) { 4226 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4227 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4228 nrows++; 4229 } 4230 } 4231 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4232 k++; 4233 buf_si += len_si[proc]; 4234 } 4235 4236 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4237 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4238 4239 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4240 for (i=0; i<merge->nrecv; i++) { 4241 ierr = PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);CHKERRQ(ierr); 4242 } 4243 4244 ierr = PetscFree(len_si);CHKERRQ(ierr); 4245 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4246 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4247 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4248 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4249 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4250 ierr = PetscFree(status);CHKERRQ(ierr); 4251 4252 /* compute a local seq matrix in each processor */ 4253 /*----------------------------------------------*/ 4254 /* allocate bi array and free space for accumulating nonzero column info */ 4255 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4256 bi[0] = 0; 4257 4258 /* create and initialize a linked list */ 4259 nlnk = N+1; 4260 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4261 4262 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4263 len = ai[owners[rank+1]] - ai[owners[rank]]; 4264 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4265 4266 current_space = free_space; 4267 4268 /* determine symbolic info for each local row */ 4269 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4270 4271 for (k=0; k<merge->nrecv; k++) { 4272 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4273 nrows = *buf_ri_k[k]; 4274 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4275 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4276 } 4277 4278 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4279 len = 0; 4280 for (i=0; i<m; i++) { 4281 bnzi = 0; 4282 /* add local non-zero cols of this proc's seqmat into lnk */ 4283 arow = owners[rank] + i; 4284 anzi = ai[arow+1] - ai[arow]; 4285 aj = a->j + ai[arow]; 4286 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4287 bnzi += nlnk; 4288 /* add received col data into lnk */ 4289 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4290 if (i == *nextrow[k]) { /* i-th row */ 4291 anzi = *(nextai[k]+1) - *nextai[k]; 4292 aj = buf_rj[k] + *nextai[k]; 4293 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4294 bnzi += nlnk; 4295 nextrow[k]++; nextai[k]++; 4296 } 4297 } 4298 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4299 4300 /* if free space is not available, make more free space */ 4301 if (current_space->local_remaining<bnzi) { 4302 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4303 nspacedouble++; 4304 } 4305 /* copy data into free space, then initialize lnk */ 4306 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4307 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4308 4309 current_space->array += bnzi; 4310 current_space->local_used += bnzi; 4311 current_space->local_remaining -= bnzi; 4312 4313 bi[i+1] = bi[i] + bnzi; 4314 } 4315 4316 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4317 4318 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4319 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4320 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4321 4322 /* create symbolic parallel matrix B_mpi */ 4323 /*---------------------------------------*/ 4324 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4325 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4326 if (n==PETSC_DECIDE) { 4327 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4328 } else { 4329 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4330 } 4331 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4332 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4333 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4334 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4335 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4336 4337 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4338 B_mpi->assembled = PETSC_FALSE; 4339 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4340 merge->bi = bi; 4341 merge->bj = bj; 4342 merge->buf_ri = buf_ri; 4343 merge->buf_rj = buf_rj; 4344 merge->coi = NULL; 4345 merge->coj = NULL; 4346 merge->owners_co = NULL; 4347 4348 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4349 4350 /* attach the supporting struct to B_mpi for reuse */ 4351 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4352 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4353 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4354 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4355 *mpimat = B_mpi; 4356 4357 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4358 PetscFunctionReturn(0); 4359 } 4360 4361 /*@C 4362 MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential 4363 matrices from each processor 4364 4365 Collective on MPI_Comm 4366 4367 Input Parameters: 4368 + comm - the communicators the parallel matrix will live on 4369 . seqmat - the input sequential matrices 4370 . m - number of local rows (or PETSC_DECIDE) 4371 . n - number of local columns (or PETSC_DECIDE) 4372 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4373 4374 Output Parameter: 4375 . mpimat - the parallel matrix generated 4376 4377 Level: advanced 4378 4379 Notes: 4380 The dimensions of the sequential matrix in each processor MUST be the same. 4381 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4382 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4383 @*/ 4384 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4385 { 4386 PetscErrorCode ierr; 4387 PetscMPIInt size; 4388 4389 PetscFunctionBegin; 4390 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4391 if (size == 1) { 4392 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4393 if (scall == MAT_INITIAL_MATRIX) { 4394 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4395 } else { 4396 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4397 } 4398 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4399 PetscFunctionReturn(0); 4400 } 4401 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4402 if (scall == MAT_INITIAL_MATRIX) { 4403 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4404 } 4405 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4406 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4407 PetscFunctionReturn(0); 4408 } 4409 4410 /*@ 4411 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4412 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4413 with MatGetSize() 4414 4415 Not Collective 4416 4417 Input Parameters: 4418 + A - the matrix 4419 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4420 4421 Output Parameter: 4422 . A_loc - the local sequential matrix generated 4423 4424 Level: developer 4425 4426 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4427 4428 @*/ 4429 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4430 { 4431 PetscErrorCode ierr; 4432 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4433 Mat_SeqAIJ *mat,*a,*b; 4434 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4435 MatScalar *aa,*ba,*cam; 4436 PetscScalar *ca; 4437 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4438 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4439 PetscBool match; 4440 MPI_Comm comm; 4441 PetscMPIInt size; 4442 4443 PetscFunctionBegin; 4444 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4445 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4446 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4447 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4448 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4449 4450 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4451 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4452 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4453 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4454 aa = a->a; ba = b->a; 4455 if (scall == MAT_INITIAL_MATRIX) { 4456 if (size == 1) { 4457 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4458 PetscFunctionReturn(0); 4459 } 4460 4461 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4462 ci[0] = 0; 4463 for (i=0; i<am; i++) { 4464 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4465 } 4466 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4467 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4468 k = 0; 4469 for (i=0; i<am; i++) { 4470 ncols_o = bi[i+1] - bi[i]; 4471 ncols_d = ai[i+1] - ai[i]; 4472 /* off-diagonal portion of A */ 4473 for (jo=0; jo<ncols_o; jo++) { 4474 col = cmap[*bj]; 4475 if (col >= cstart) break; 4476 cj[k] = col; bj++; 4477 ca[k++] = *ba++; 4478 } 4479 /* diagonal portion of A */ 4480 for (j=0; j<ncols_d; j++) { 4481 cj[k] = cstart + *aj++; 4482 ca[k++] = *aa++; 4483 } 4484 /* off-diagonal portion of A */ 4485 for (j=jo; j<ncols_o; j++) { 4486 cj[k] = cmap[*bj++]; 4487 ca[k++] = *ba++; 4488 } 4489 } 4490 /* put together the new matrix */ 4491 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4492 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4493 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4494 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4495 mat->free_a = PETSC_TRUE; 4496 mat->free_ij = PETSC_TRUE; 4497 mat->nonew = 0; 4498 } else if (scall == MAT_REUSE_MATRIX) { 4499 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4500 ci = mat->i; cj = mat->j; cam = mat->a; 4501 for (i=0; i<am; i++) { 4502 /* off-diagonal portion of A */ 4503 ncols_o = bi[i+1] - bi[i]; 4504 for (jo=0; jo<ncols_o; jo++) { 4505 col = cmap[*bj]; 4506 if (col >= cstart) break; 4507 *cam++ = *ba++; bj++; 4508 } 4509 /* diagonal portion of A */ 4510 ncols_d = ai[i+1] - ai[i]; 4511 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4512 /* off-diagonal portion of A */ 4513 for (j=jo; j<ncols_o; j++) { 4514 *cam++ = *ba++; bj++; 4515 } 4516 } 4517 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4518 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4519 PetscFunctionReturn(0); 4520 } 4521 4522 /*@C 4523 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns 4524 4525 Not Collective 4526 4527 Input Parameters: 4528 + A - the matrix 4529 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4530 - row, col - index sets of rows and columns to extract (or NULL) 4531 4532 Output Parameter: 4533 . A_loc - the local sequential matrix generated 4534 4535 Level: developer 4536 4537 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4538 4539 @*/ 4540 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4541 { 4542 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4543 PetscErrorCode ierr; 4544 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4545 IS isrowa,iscola; 4546 Mat *aloc; 4547 PetscBool match; 4548 4549 PetscFunctionBegin; 4550 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4551 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4552 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4553 if (!row) { 4554 start = A->rmap->rstart; end = A->rmap->rend; 4555 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4556 } else { 4557 isrowa = *row; 4558 } 4559 if (!col) { 4560 start = A->cmap->rstart; 4561 cmap = a->garray; 4562 nzA = a->A->cmap->n; 4563 nzB = a->B->cmap->n; 4564 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4565 ncols = 0; 4566 for (i=0; i<nzB; i++) { 4567 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4568 else break; 4569 } 4570 imark = i; 4571 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4572 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4573 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4574 } else { 4575 iscola = *col; 4576 } 4577 if (scall != MAT_INITIAL_MATRIX) { 4578 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4579 aloc[0] = *A_loc; 4580 } 4581 ierr = MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4582 *A_loc = aloc[0]; 4583 ierr = PetscFree(aloc);CHKERRQ(ierr); 4584 if (!row) { 4585 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4586 } 4587 if (!col) { 4588 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4589 } 4590 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4591 PetscFunctionReturn(0); 4592 } 4593 4594 /*@C 4595 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4596 4597 Collective on Mat 4598 4599 Input Parameters: 4600 + A,B - the matrices in mpiaij format 4601 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4602 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4603 4604 Output Parameter: 4605 + rowb, colb - index sets of rows and columns of B to extract 4606 - B_seq - the sequential matrix generated 4607 4608 Level: developer 4609 4610 @*/ 4611 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4612 { 4613 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4614 PetscErrorCode ierr; 4615 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4616 IS isrowb,iscolb; 4617 Mat *bseq=NULL; 4618 4619 PetscFunctionBegin; 4620 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4621 SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 4622 } 4623 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4624 4625 if (scall == MAT_INITIAL_MATRIX) { 4626 start = A->cmap->rstart; 4627 cmap = a->garray; 4628 nzA = a->A->cmap->n; 4629 nzB = a->B->cmap->n; 4630 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4631 ncols = 0; 4632 for (i=0; i<nzB; i++) { /* row < local row index */ 4633 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4634 else break; 4635 } 4636 imark = i; 4637 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4638 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4639 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4640 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4641 } else { 4642 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4643 isrowb = *rowb; iscolb = *colb; 4644 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4645 bseq[0] = *B_seq; 4646 } 4647 ierr = MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4648 *B_seq = bseq[0]; 4649 ierr = PetscFree(bseq);CHKERRQ(ierr); 4650 if (!rowb) { 4651 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4652 } else { 4653 *rowb = isrowb; 4654 } 4655 if (!colb) { 4656 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4657 } else { 4658 *colb = iscolb; 4659 } 4660 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4661 PetscFunctionReturn(0); 4662 } 4663 4664 /* 4665 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4666 of the OFF-DIAGONAL portion of local A 4667 4668 Collective on Mat 4669 4670 Input Parameters: 4671 + A,B - the matrices in mpiaij format 4672 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4673 4674 Output Parameter: 4675 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4676 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4677 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4678 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4679 4680 Level: developer 4681 4682 */ 4683 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4684 { 4685 VecScatter_MPI_General *gen_to,*gen_from; 4686 PetscErrorCode ierr; 4687 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4688 Mat_SeqAIJ *b_oth; 4689 VecScatter ctx =a->Mvctx; 4690 MPI_Comm comm; 4691 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4692 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4693 PetscInt *rvalues,*svalues; 4694 MatScalar *b_otha,*bufa,*bufA; 4695 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4696 MPI_Request *rwaits = NULL,*swaits = NULL; 4697 MPI_Status *sstatus,rstatus; 4698 PetscMPIInt jj,size; 4699 PetscInt *cols,sbs,rbs; 4700 PetscScalar *vals; 4701 4702 PetscFunctionBegin; 4703 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4704 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4705 4706 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4707 SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%d, %d) != (%d,%d)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 4708 } 4709 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4710 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4711 4712 if (size == 1) { 4713 startsj_s = NULL; 4714 bufa_ptr = NULL; 4715 *B_oth = NULL; 4716 PetscFunctionReturn(0); 4717 } 4718 4719 gen_to = (VecScatter_MPI_General*)ctx->todata; 4720 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4721 nrecvs = gen_from->n; 4722 nsends = gen_to->n; 4723 4724 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4725 srow = gen_to->indices; /* local row index to be sent */ 4726 sstarts = gen_to->starts; 4727 sprocs = gen_to->procs; 4728 sstatus = gen_to->sstatus; 4729 sbs = gen_to->bs; 4730 rstarts = gen_from->starts; 4731 rprocs = gen_from->procs; 4732 rbs = gen_from->bs; 4733 4734 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4735 if (scall == MAT_INITIAL_MATRIX) { 4736 /* i-array */ 4737 /*---------*/ 4738 /* post receives */ 4739 ierr = PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);CHKERRQ(ierr); 4740 for (i=0; i<nrecvs; i++) { 4741 rowlen = rvalues + rstarts[i]*rbs; 4742 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4743 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4744 } 4745 4746 /* pack the outgoing message */ 4747 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4748 4749 sstartsj[0] = 0; 4750 rstartsj[0] = 0; 4751 len = 0; /* total length of j or a array to be sent */ 4752 k = 0; 4753 ierr = PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);CHKERRQ(ierr); 4754 for (i=0; i<nsends; i++) { 4755 rowlen = svalues + sstarts[i]*sbs; 4756 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4757 for (j=0; j<nrows; j++) { 4758 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4759 for (l=0; l<sbs; l++) { 4760 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4761 4762 rowlen[j*sbs+l] = ncols; 4763 4764 len += ncols; 4765 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4766 } 4767 k++; 4768 } 4769 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4770 4771 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4772 } 4773 /* recvs and sends of i-array are completed */ 4774 i = nrecvs; 4775 while (i--) { 4776 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4777 } 4778 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4779 ierr = PetscFree(svalues);CHKERRQ(ierr); 4780 4781 /* allocate buffers for sending j and a arrays */ 4782 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4783 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4784 4785 /* create i-array of B_oth */ 4786 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4787 4788 b_othi[0] = 0; 4789 len = 0; /* total length of j or a array to be received */ 4790 k = 0; 4791 for (i=0; i<nrecvs; i++) { 4792 rowlen = rvalues + rstarts[i]*rbs; 4793 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 4794 for (j=0; j<nrows; j++) { 4795 b_othi[k+1] = b_othi[k] + rowlen[j]; 4796 ierr = PetscIntSumError(rowlen[j],len,&len);CHKERRQ(ierr); 4797 k++; 4798 } 4799 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4800 } 4801 ierr = PetscFree(rvalues);CHKERRQ(ierr); 4802 4803 /* allocate space for j and a arrrays of B_oth */ 4804 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4805 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4806 4807 /* j-array */ 4808 /*---------*/ 4809 /* post receives of j-array */ 4810 for (i=0; i<nrecvs; i++) { 4811 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4812 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4813 } 4814 4815 /* pack the outgoing message j-array */ 4816 k = 0; 4817 for (i=0; i<nsends; i++) { 4818 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4819 bufJ = bufj+sstartsj[i]; 4820 for (j=0; j<nrows; j++) { 4821 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4822 for (ll=0; ll<sbs; ll++) { 4823 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4824 for (l=0; l<ncols; l++) { 4825 *bufJ++ = cols[l]; 4826 } 4827 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4828 } 4829 } 4830 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4831 } 4832 4833 /* recvs and sends of j-array are completed */ 4834 i = nrecvs; 4835 while (i--) { 4836 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4837 } 4838 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4839 } else if (scall == MAT_REUSE_MATRIX) { 4840 sstartsj = *startsj_s; 4841 rstartsj = *startsj_r; 4842 bufa = *bufa_ptr; 4843 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4844 b_otha = b_oth->a; 4845 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4846 4847 /* a-array */ 4848 /*---------*/ 4849 /* post receives of a-array */ 4850 for (i=0; i<nrecvs; i++) { 4851 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4852 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4853 } 4854 4855 /* pack the outgoing message a-array */ 4856 k = 0; 4857 for (i=0; i<nsends; i++) { 4858 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4859 bufA = bufa+sstartsj[i]; 4860 for (j=0; j<nrows; j++) { 4861 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4862 for (ll=0; ll<sbs; ll++) { 4863 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4864 for (l=0; l<ncols; l++) { 4865 *bufA++ = vals[l]; 4866 } 4867 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4868 } 4869 } 4870 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4871 } 4872 /* recvs and sends of a-array are completed */ 4873 i = nrecvs; 4874 while (i--) { 4875 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4876 } 4877 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4878 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4879 4880 if (scall == MAT_INITIAL_MATRIX) { 4881 /* put together the new matrix */ 4882 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4883 4884 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4885 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4886 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4887 b_oth->free_a = PETSC_TRUE; 4888 b_oth->free_ij = PETSC_TRUE; 4889 b_oth->nonew = 0; 4890 4891 ierr = PetscFree(bufj);CHKERRQ(ierr); 4892 if (!startsj_s || !bufa_ptr) { 4893 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4894 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4895 } else { 4896 *startsj_s = sstartsj; 4897 *startsj_r = rstartsj; 4898 *bufa_ptr = bufa; 4899 } 4900 } 4901 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4902 PetscFunctionReturn(0); 4903 } 4904 4905 /*@C 4906 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4907 4908 Not Collective 4909 4910 Input Parameters: 4911 . A - The matrix in mpiaij format 4912 4913 Output Parameter: 4914 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4915 . colmap - A map from global column index to local index into lvec 4916 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4917 4918 Level: developer 4919 4920 @*/ 4921 #if defined(PETSC_USE_CTABLE) 4922 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4923 #else 4924 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4925 #endif 4926 { 4927 Mat_MPIAIJ *a; 4928 4929 PetscFunctionBegin; 4930 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4931 PetscValidPointer(lvec, 2); 4932 PetscValidPointer(colmap, 3); 4933 PetscValidPointer(multScatter, 4); 4934 a = (Mat_MPIAIJ*) A->data; 4935 if (lvec) *lvec = a->lvec; 4936 if (colmap) *colmap = a->colmap; 4937 if (multScatter) *multScatter = a->Mvctx; 4938 PetscFunctionReturn(0); 4939 } 4940 4941 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4942 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4943 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4944 #if defined(PETSC_HAVE_ELEMENTAL) 4945 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4946 #endif 4947 #if defined(PETSC_HAVE_HYPRE) 4948 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*); 4949 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 4950 #endif 4951 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*); 4952 4953 /* 4954 Computes (B'*A')' since computing B*A directly is untenable 4955 4956 n p p 4957 ( ) ( ) ( ) 4958 m ( A ) * n ( B ) = m ( C ) 4959 ( ) ( ) ( ) 4960 4961 */ 4962 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4963 { 4964 PetscErrorCode ierr; 4965 Mat At,Bt,Ct; 4966 4967 PetscFunctionBegin; 4968 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4969 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4970 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4971 ierr = MatDestroy(&At);CHKERRQ(ierr); 4972 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 4973 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4974 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 4975 PetscFunctionReturn(0); 4976 } 4977 4978 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4979 { 4980 PetscErrorCode ierr; 4981 PetscInt m=A->rmap->n,n=B->cmap->n; 4982 Mat Cmat; 4983 4984 PetscFunctionBegin; 4985 if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n); 4986 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4987 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4988 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 4989 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 4990 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4991 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4992 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4993 4994 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 4995 4996 *C = Cmat; 4997 PetscFunctionReturn(0); 4998 } 4999 5000 /* ----------------------------------------------------------------*/ 5001 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5002 { 5003 PetscErrorCode ierr; 5004 5005 PetscFunctionBegin; 5006 if (scall == MAT_INITIAL_MATRIX) { 5007 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5008 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5009 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5010 } 5011 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5012 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5013 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5014 PetscFunctionReturn(0); 5015 } 5016 5017 /*MC 5018 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5019 5020 Options Database Keys: 5021 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5022 5023 Level: beginner 5024 5025 .seealso: MatCreateAIJ() 5026 M*/ 5027 5028 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5029 { 5030 Mat_MPIAIJ *b; 5031 PetscErrorCode ierr; 5032 PetscMPIInt size; 5033 5034 PetscFunctionBegin; 5035 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5036 5037 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5038 B->data = (void*)b; 5039 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5040 B->assembled = PETSC_FALSE; 5041 B->insertmode = NOT_SET_VALUES; 5042 b->size = size; 5043 5044 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5045 5046 /* build cache for off array entries formed */ 5047 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5048 5049 b->donotstash = PETSC_FALSE; 5050 b->colmap = 0; 5051 b->garray = 0; 5052 b->roworiented = PETSC_TRUE; 5053 5054 /* stuff used for matrix vector multiply */ 5055 b->lvec = NULL; 5056 b->Mvctx = NULL; 5057 5058 /* stuff for MatGetRow() */ 5059 b->rowindices = 0; 5060 b->rowvalues = 0; 5061 b->getrowactive = PETSC_FALSE; 5062 5063 /* flexible pointer used in CUSP/CUSPARSE classes */ 5064 b->spptr = NULL; 5065 5066 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5067 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5068 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5069 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5070 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5071 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5072 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5073 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5074 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5075 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5076 #if defined(PETSC_HAVE_ELEMENTAL) 5077 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5078 #endif 5079 #if defined(PETSC_HAVE_HYPRE) 5080 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 5081 #endif 5082 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);CHKERRQ(ierr); 5083 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5084 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5085 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5086 #if defined(PETSC_HAVE_HYPRE) 5087 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 5088 #endif 5089 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5090 PetscFunctionReturn(0); 5091 } 5092 5093 /*@C 5094 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5095 and "off-diagonal" part of the matrix in CSR format. 5096 5097 Collective on MPI_Comm 5098 5099 Input Parameters: 5100 + comm - MPI communicator 5101 . m - number of local rows (Cannot be PETSC_DECIDE) 5102 . n - This value should be the same as the local size used in creating the 5103 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5104 calculated if N is given) For square matrices n is almost always m. 5105 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5106 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5107 . i - row indices for "diagonal" portion of matrix 5108 . j - column indices 5109 . a - matrix values 5110 . oi - row indices for "off-diagonal" portion of matrix 5111 . oj - column indices 5112 - oa - matrix values 5113 5114 Output Parameter: 5115 . mat - the matrix 5116 5117 Level: advanced 5118 5119 Notes: 5120 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5121 must free the arrays once the matrix has been destroyed and not before. 5122 5123 The i and j indices are 0 based 5124 5125 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5126 5127 This sets local rows and cannot be used to set off-processor values. 5128 5129 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5130 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5131 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5132 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5133 keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5134 communication if it is known that only local entries will be set. 5135 5136 .keywords: matrix, aij, compressed row, sparse, parallel 5137 5138 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5139 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5140 @*/ 5141 PetscErrorCode MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[],PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5142 { 5143 PetscErrorCode ierr; 5144 Mat_MPIAIJ *maij; 5145 5146 PetscFunctionBegin; 5147 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5148 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5149 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5150 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5151 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5152 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5153 maij = (Mat_MPIAIJ*) (*mat)->data; 5154 5155 (*mat)->preallocated = PETSC_TRUE; 5156 5157 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5158 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5159 5160 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5161 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5162 5163 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5164 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5165 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5166 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5167 5168 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 5169 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5170 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5171 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 5172 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5173 PetscFunctionReturn(0); 5174 } 5175 5176 /* 5177 Special version for direct calls from Fortran 5178 */ 5179 #include <petsc/private/fortranimpl.h> 5180 5181 /* Change these macros so can be used in void function */ 5182 #undef CHKERRQ 5183 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5184 #undef SETERRQ2 5185 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5186 #undef SETERRQ3 5187 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5188 #undef SETERRQ 5189 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5190 5191 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5192 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5193 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5194 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5195 #else 5196 #endif 5197 PETSC_EXTERN void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5198 { 5199 Mat mat = *mmat; 5200 PetscInt m = *mm, n = *mn; 5201 InsertMode addv = *maddv; 5202 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5203 PetscScalar value; 5204 PetscErrorCode ierr; 5205 5206 MatCheckPreallocated(mat,1); 5207 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5208 5209 #if defined(PETSC_USE_DEBUG) 5210 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5211 #endif 5212 { 5213 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5214 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5215 PetscBool roworiented = aij->roworiented; 5216 5217 /* Some Variables required in the macro */ 5218 Mat A = aij->A; 5219 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5220 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5221 MatScalar *aa = a->a; 5222 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5223 Mat B = aij->B; 5224 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5225 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5226 MatScalar *ba = b->a; 5227 5228 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5229 PetscInt nonew = a->nonew; 5230 MatScalar *ap1,*ap2; 5231 5232 PetscFunctionBegin; 5233 for (i=0; i<m; i++) { 5234 if (im[i] < 0) continue; 5235 #if defined(PETSC_USE_DEBUG) 5236 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 5237 #endif 5238 if (im[i] >= rstart && im[i] < rend) { 5239 row = im[i] - rstart; 5240 lastcol1 = -1; 5241 rp1 = aj + ai[row]; 5242 ap1 = aa + ai[row]; 5243 rmax1 = aimax[row]; 5244 nrow1 = ailen[row]; 5245 low1 = 0; 5246 high1 = nrow1; 5247 lastcol2 = -1; 5248 rp2 = bj + bi[row]; 5249 ap2 = ba + bi[row]; 5250 rmax2 = bimax[row]; 5251 nrow2 = bilen[row]; 5252 low2 = 0; 5253 high2 = nrow2; 5254 5255 for (j=0; j<n; j++) { 5256 if (roworiented) value = v[i*n+j]; 5257 else value = v[i+j*m]; 5258 if (in[j] >= cstart && in[j] < cend) { 5259 col = in[j] - cstart; 5260 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5261 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5262 } else if (in[j] < 0) continue; 5263 #if defined(PETSC_USE_DEBUG) 5264 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 5265 #endif 5266 else { 5267 if (mat->was_assembled) { 5268 if (!aij->colmap) { 5269 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5270 } 5271 #if defined(PETSC_USE_CTABLE) 5272 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5273 col--; 5274 #else 5275 col = aij->colmap[in[j]] - 1; 5276 #endif 5277 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5278 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5279 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5280 col = in[j]; 5281 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5282 B = aij->B; 5283 b = (Mat_SeqAIJ*)B->data; 5284 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5285 rp2 = bj + bi[row]; 5286 ap2 = ba + bi[row]; 5287 rmax2 = bimax[row]; 5288 nrow2 = bilen[row]; 5289 low2 = 0; 5290 high2 = nrow2; 5291 bm = aij->B->rmap->n; 5292 ba = b->a; 5293 } 5294 } else col = in[j]; 5295 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5296 } 5297 } 5298 } else if (!aij->donotstash) { 5299 if (roworiented) { 5300 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5301 } else { 5302 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5303 } 5304 } 5305 } 5306 } 5307 PetscFunctionReturnVoid(); 5308 } 5309 5310